T. Brad Kielinski is a Philadelphia-area technology recruiter who helps companies hire tech professionals. They also share job-search advice, recruiting insights, and local technology job openings.
Useful for Philadelphia tech hiring insights, employer search briefs, and candidate-side job-search advice.
Best for
Co-branded editorial or workshop for local startups hiring senior technical talent.
Not for
Exclusive enterprise ATS lead generation or Fortune 500 HR campaigns with guarantees.
Key takeaways
A role-and-skills formula for LinkedIn headlines helps candidates describe themselves.
Posts describe hidden filters and how candidates get screened and hired.
They share Philadelphia funding news, local openings, and community events.
Check first: Confirm audience demographics, post performance, and sources for hiring statistics.
Main ideas
Run a direct-access campaign, not an application-volume contest · Learn the hidden filters, even when they are unfair · AI hiring runs on networks and proof, not public postings
Audience
27,824 LinkedIn followers · 5,000+ members IT Pros – Philadelphia community membership
Brad Kielinski is a Philadelphia-area technology recruiter whose LinkedIn posts combine practical job-search advice, recruiting perspectives, and updates on local tech companies and opportunities.
Readers will find concrete guidance—such as a role-and-skills formula for LinkedIn headlines—alongside explanations of how they think candidates get screened and hired.
They also share local funding news, job openings, and events that connect Philadelphia’s technology community.
Kielinski makes recruiting advice tangible, pairing each point with examples or an action.
Their headline posts show how candidates at different career stages can describe their skills and industry; their job-search posts turn familiar frustrations, from application silence to interview ghosting, into a recognizable sequence.
Their recruiting posts also spell out role requirements, including openings for a zero-trust systems engineer and a forward-deployed AI engineer.
Beyond individual careers, they connect hiring to the Philadelphia tech scene through company news, local openings, and events.
The tone can be deliberately blunt, and some posts make broad claims about hiring statistics or particular employers without substantiation.
Brad Kielinski's recurring argument is that tech hiring is less open than it looks.
Candidates who win run a direct-access campaign, learn the filters recruiters and hiring teams actually use, and make their first line specific.
Employers win or lose talent through local reputation, working conditions, and networks; in AI hiring especially, public job postings are a minor route compared with poaching, referrals, and visible proof of shipped work.
They pair blunt diagnosis with tactical fixes, often naming the bias or employer problem and then telling the reader what to do about it.
Run a direct-access campaign, not an application-volume contest
Kielinski argues that long tech searches usually fail on strategy, not skill.
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Most candidates apply to hundreds of quick-apply postings, get filtered by ATS and generic HR screens, and dilute their positioning.
A stronger approach is to map target employers by sector, funding stage, size, engineering culture, and team problem; position yourself around a specific bottleneck; and run several interview processes in parallel to create urgency and feedback.
They say the difference between a messy nine-month search and a focused nine-week search is usually not effort but knowing who can help you get there.
In a post on why 90% of searches take six months, Kielinski contrasts 200+ quick-apply applications with target mapping, laser-focused positioning, and parallel pipeline processing. A later post on layoffs describes the sequence as layoff, pause, exploration, and next move, noting that the first move is often not the final one.
Learn the hidden filters, even when they are unfair
Kielinski argues that hiring teams reject resumes in seconds for reasons candidates rarely see, and that candidates need to know those reasons even when they are biased.
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The filters they name include Big Tech or consultancy backgrounds, pre-seed-only leadership, frequent job changes, manual QA experience, missing profile photos, and employment gaps.
They say the goal is to expose the biases, not defend them, then offer fixes: strip corporate jargon and show 0-to-1 work, group contract roles under one title, state layoffs next to the company name, move automation upskilling to the top, add a professional photo, and keep a profile active.
The advice acknowledges unfair filters while asking candidates to work around them.
In the 'Unspoken Filters' post, Kielinski describes sitting in calibration meetings and hearing the exact reasons hiring teams reject resumes. One example is a candidate with five or more years at Big Tech and no progression getting flagged; the suggested fix is to show where they built from zero to one, wore multiple hats, or owned a product metric.
AI hiring runs on networks and proof, not public postings
Kielinski argues that public AI job postings are mostly corporate fiction.
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Citing the 2026 AI Engineer Hiring Report, they say public postings account for less than 15% of actual AI hires.
The rest comes through specialist recruiters who track candidates on GitHub and Hugging Face, employee referrals through lab peers and co-authors, direct networking at hackathons and builder meetups, and job boards.
They add that AI tools mass-applying meet employer tools auto-rejecting, and that up to 20% of listings may be ghost jobs.
A separate role brief sharpens the point: the AI-native startup wants a forward-deployed engineer who has shipped in messy warehouses and ERP systems, not someone who only prompts Claude from a couch.
For a Forward Deployed Engineer search, Kielinski describes a $200,000–$250,000 base role with about 60% travel and three days a week embedded with enterprise customers, mapping workflows, writing integration glue, and deploying agentic AI. Retail, e-commerce, CPG, or supply-chain domain knowledge is non-negotiable.
Employer reputation and working conditions decide who can hire
Kielinski argues that local tech employers earn or lose candidates through how they actually operate.
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A post listing seven Philadelphia-area companies frequently placed on no-hire or do-not-recruit lists gives reasons: outsourcing reversals at Vanguard, technical debt and disorganized IT at Comcast, a stagnant stack at Independence Blue Cross, buggy legacy systems and bureaucracy at SEPTA, repeated IT reorganizations at Aramark, cyberattack stress at Temple Health, and disconnected tech leadership at Day & Zimmermann.
The opposite case appears in MSP job posts that sell no on-call, 7+ year average tenure, benefits, and a path to vCIO.
Their point is practical: burnout, chaos, and poor tech leadership are hiring problems, not just employee problems.
Ask for the underlying lists; the post does not verify a ranking.
The no-hire post says SEPTA IT workers maintain notoriously buggy systems, including SEPTA Key, and face heavy bureaucracy and slow procurement. An MSP post for a senior IT specialist counters with 'Zero On-Call,' 75% company-paid health and vision, automatic 3% 401k contribution, 18 days PTO, and technicians staying an average of 7+ years.
Kielinski argues that a LinkedIn headline should do the work a recruiter would otherwise have to guess at.
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The recurring formula is role, top three skills or certifications, and industry, separated by pipes or bullets.
They give examples by career stage, from early-career full-stack, data, and security roles through mid-level DevOps and mobile roles to senior architecture and executive leadership.
The advice: use the market title when an internal title hides the actual work, remove question marks and guesswork, and make the stack readable at a glance.
They also supply Boolean search strings that recruiters use to find profiles by title and city, reinforcing that discoverability is part of positioning.
One early-career example is 'Full Stack Engineer | React, Node.js, AWS | FinTech & E-Commerce Systems.' A leadership example is 'VP of Engineering | Global Team Scale-Up, Architecture Strategy, Agile Transformation | High-Volume E-Commerce & Retail Tech.'
Treat the search as a psychological marathon, not a single rejection
Kielinski argues that a tech job search has an emotional arc that candidates and outplacement programs need to address.
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They map five stages: unbounded optimism, the ATS black hole, the interview gauntlet and ghosting, the existential pivot, and practical enlightenment.
The final stage trades title prestige and perks for a sane team, an honest product, clear expectations, and a steady paycheck.
In a layoff post, they cite survey figures: 63% of 1,000 laid-off tech professionals started their own company, 40% of those waited 6–12 months, and nearly 2 in 5 who found new jobs changed occupations or industries.
Their conclusion is that the first move after a layoff is often not the final move, and that a mentor can shorten a messy search.
The five-stage post gives concrete details: 1,200 applicants for one role within two hours, a 12-hour take-home assignment for a company that may not be hiring, and ghost jobs kept open for pipeline or market perception. The layoff post describes the sequence as layoff, pause, exploration, and next move.
What does a recruiter see first, and how can candidates make that first line work for them?
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Kielinski treats a LinkedIn headline as a mini-billboard: a targeted tech title, the top three core technologies or certifications, and industry or sector expertise, separated by pipes.
The post gives examples by career stage, from early-career full-stack and data roles to senior architecture and executive roles.
It advises candidates to use the market title when an internal title obscures the actual work and to keep separators readable.
For brands planning a campaign
This repeatable, candidate-facing format could become a co-branded checklist, workshop, or before-and-after headline review. It’s strongest for attracting job seekers; a hiring-manager collaboration would need a companion piece on how recruiters screen headlines.
Which biases and shortcuts shape hiring decisions before a candidate reaches an interview?
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Kielinski draws on calibration meetings to list five filters: Big Tech or consultancy experience, pre-seed leadership, frequent job changes, manual QA backgrounds, and missing photos or employment gaps.
For each, the post names the bias and a fix.
Examples include grouping contract roles under one title, explaining layoffs next to the company name, and moving automation upskilling projects to the top of a resume.
The goal, Kielinski says, is to expose the biases, not defend them.
For brands planning a campaign
A recruiting firm could use this two-sided format—bias, then practical fix—for a hiring-trends collaboration aimed at candidates and employers.
The subject is high-interest and shareable, but the claims reflect recruiter observations, not audited hiring data.
Which local employers do tech candidates avoid, and why?
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Kielinski names seven Philadelphia-area employers—Vanguard, Comcast, Independence Blue Cross, SEPTA, Aramark, Temple University Health System, and Day & Zimmermann—and gives a specific reason for each.
The reasons include outsourcing reversals, technical debt, a stagnant stack, buggy legacy systems, repeated IT reorganizations, cyberattack stress, and leadership disconnected from technology teams.
The post says these companies frequently appear on no-hire or do-not-recruit lists, but does not show the list or verify the claims.
Ask for the underlying list and support for each claim before republishing.
For brands planning a campaign
This could spark a strong local-market conversation for a recruiting firm, but it carries reputational risk.
A collaboration could pair the list with a balanced employer response or verified candidate-sentiment research.
To publish it as fact, ask for supporting evidence.
Where do senior AI hires actually come from if public job postings aren’t the main route?
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Kielinski argues that public postings account for less than 15% of AI hires, citing the 2026 AI Engineer Hiring Report.
The post breaks the rest into recruiter poaching (35–45%), employee referrals (30–40%), direct networking (10–15%), and job boards (10–15%), then adds that up to 20% of listings may be ghost jobs.
It describes AI candidates being tracked on GitHub and Hugging Face, hired through lab peers and co-authors, or noticed through open-source fixes and Kaggle results.
The tone is blunt: a founder hiring through a standard job board is 'buying a lottery ticket.'
For brands planning a campaign
This could anchor a collaboration on AI hiring trends for founders and hiring managers.
The statistics are the hook, but the post doesn’t include its report link or method.
Ask for the source data and a clear distinction between cited report figures and Kielinski's own percentages.
How does Kielinski connect a local funding round to the jobs that follow?
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The post summarizes Lula Commerce's $8m Series A and more than $16m total raised, then explains the market gap: more than 155,000 U.S. convenience stores serve 160 million visitors daily, but fewer than 10% offer modern online ordering or delivery.
It lists two open roles, their experience requirements, and a stack.
The post closes with Kielinski's recruiting and job-search services, including a claim of more than 1,000 successful Philly-region hires.
For brands planning a campaign
The format—funding news, why it matters, then open roles—offers a practical local-ecosystem content unit. A recruiting firm could collaborate on a recurring Philly funding-and-hiring digest, though the service pitch at the end makes this more lead generation than neutral market reporting.
How does Kielinski turn online recruiting reach into an in-person tech community?
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The post invites tech leaders and executives, engineers and architects, ecosystem builders, and IT Pros - Philadelphia members to a data-center tour at Flexential in Collegeville, followed by food, drinks, and networking at The Analog Room in Phoenixville.
It gives the date, time, distance between venues, and a registration link in the comments.
The audience mix targets both hiring-side leaders and technical practitioners.
For brands planning a campaign
This offers a concrete event model for a recruiting firm: a technical venue tour and structured networking, with a built-in community partner.
A collaboration could co-host a similar Philadelphia event or turn the format into a content series.
Replace the weak registration-in-comments call to action in any co-branded version.
What does a modern tech job search feel like from the candidate's side?
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Kielinski maps five stages: unbounded optimism, the ATS black hole, the interview gauntlet and ghosting, the existential pivot, and practical enlightenment.
Specifics bring them to life: applicants treating recruiter messages as clutter, 1,200 people applying to one role within two hours, a 12-hour take-home assignment, ghost jobs, and a final shift toward direct outreach to hiring managers.
The arc moves from salary and remote-work demands to a sane team, an honest product, clear expectations, and a steady paycheck.
For brands planning a campaign
This could support outplacement or job-search content because it names the emotional and tactical steps candidates actually go through. A recruiting firm could use it as the narrative spine for a candidate-focused collaboration; for hiring managers, pair it with data on how employers run interview loops.
Local IT and MSP hiring, plus candidate promotion3
AI and automation in hiring2
Remote-work security and fraud1
Recruiting for hard-to-fill technical roles
Kielinski publishes detailed recruiting briefs for senior technical and IT roles.
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Examples include a Staff Engineer for Zero Trust Infrastructure at $200,000–$230,000, a Senior Mobile Platform Engineer at $200,000–$230,000, a Forward Deployed Engineer at $200,000–$250,000, and a Senior Director of Global IT. The posts name the stack, location, must-haves, and disqualifiers; several say a recruiter has been engaged to conduct the search.
The recurring format is a structured role brief: compensation and location first, followed by technical requirements, target profile, explicit exclusions, and a direct invitation to message them.
For brands planning a campaign
Useful for co-created employer content on niche technical hiring: turn briefs into demand-signal pieces, role explainers, or candidate-audience posts for a recruiting firm. Explicit disqualifiers sharpen the content but make it more exclusionary than a general market-trend post.
Kielinski publishes Philadelphia-area IT support and MSP job posts with concrete terms: $80,000–$85,000 to start, no on-call, 7+ years of MSP experience, client-site travel, benefits, and a path toward vCIO work.
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A separate post promotes local job seeker Matthew Vallance, outlining their background, commute range, technical stack, and salary target, and noting there is no recruiter fee.
The format is practical and transactional: role or candidate facts first, followed by requirements, perks, and a private-message call to action.
For brands planning a campaign
A recruiting firm could use this style for local employer-brand posts or talent-community spotlights. The posts are more granular and local than the senior product-engineering briefs, so a collaboration should distinguish local IT/MSP audiences from startup and scale-up technical audiences.
Kielinski repeatedly teaches a LinkedIn headline formula: role, top three skills or certifications, and industry.
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Examples span career stages, from early-career software, data, and security roles through mid-level DevOps and mobile roles to senior architecture and executive leadership. A related post supplies Boolean search strings for finding LinkedIn profiles by title and city.
The approach is template-driven: offer copyable examples, explain what recruiters scan for, and reduce the headline to a clear, keyword-rich structure.
For brands planning a campaign
Strong fit for job-seeker education content, such as a co-branded headline worksheet, live profile review, or recruiter-visibility guide. The Boolean-search post also shows they can speak to sourcing mechanics; frame that material carefully so it doesn’t read as a loophole or spam tactic.
Kielinski writes candidly about the hidden filters and emotional stages of a tech job search.
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Posts name biases around Big Tech or consultancy backgrounds, pre-seed leadership, frequent job changes, manual QA, missing profile photos, and employment gaps.
Another describes five stages: unbounded optimism, the ATS black hole, interview ghosting, an existential pivot, and practical enlightenment.
Kielinski also contrasts long searches with a top-1% direct-access campaign built on target mapping, focused positioning, and parallel interview pipelines.
The format pairs insider diagnosis with prescriptive fixes, often in a numbered list. Kielinski also promotes a free live group workshop on how hiring really works behind the scenes.
For brands planning a campaign
Well suited to myth-busting guides, webinars, and outplacement content for job seekers. The material directly addresses unfair biases and advises readers to adapt to them; a brand should decide whether that realism fits its tone or needs a balancing note.
Kielinski argues that public AI job postings account for a small share of actual AI hires.
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One post cites the 2026 AI Engineer Hiring Report for the claim that public postings account for less than 15% of AI hires, with the rest coming through specialist recruiters, referrals, direct networking, and job boards.
They describe AI tools mass-applying while employer tools auto-reject, and note ghost jobs.
A separate role brief seeks a Forward Deployed Engineer for an AI-native process-automation startup, requiring retail, e-commerce, CPG, or supply-chain domain experience.
The format combines reported statistics, satirical insider commentary, and a concrete role example.
The AI commentary is more speculative and source-light than the local job posts, which state compensation and requirements directly.
For brands planning a campaign
Useful for AI hiring trend content aimed at employers and senior candidates. Verify the cited statistics before reuse: the post names a report but doesn’t link to it or show its methodology.
Kielinski reports local funding and hiring news: Lula Commerce’s $8m Series A, Voomi Supply’s $10m Series A, and Ethermed’s $8.5m Series A.
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One post lists seven Philadelphia-area employers that frequently appear on “no-hire” or “do not recruit” lists and gives reasons for each. Kielinski also promotes the IT Pros Philadelphia community of 5,000+ members, a Tech on Tap data-center tour, and remote work from a West Chester home office.
The format uses short local-news posts to connect a funding round, event, or employer-reputation issue to hiring implications; some include live job openings.
This local-news stream extends beyond Kielinski’s job-search advice to event promotion and community building, as well as recruiting commentary.
For brands planning a campaign
A recruiting firm could collaborate on Philadelphia market reporting, community-event content, or local employer-brand campaigns. The no-hire list is opinionated and names employers, so treat it as candid local commentary, not neutral market data.
Kielinski traces scam formats from advance-fee fraud and fake grandparent calls to AI voice cloning, romance crypto schemes and “profile renting,” in which an offshore developer uses a domestic worker’s identity and credentials.
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They connect profile renting to legal liability, security risk and the corporate push for return-to-office policies.
A short evolutionary list moves from older scams to current remote-work risks.
Security and labor-market commentary, not recruiting how-to.
For brands planning a campaign
Relevant to cybersecurity, identity verification, background screening and remote-work policy content. It expands the collaboration beyond job-search advice into future-of-work and hiring-risk commentary.
Kielinski's disclosed business relationship is IT Pros – Philadelphia, the regional tech community they founded.
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Their posts also name Philadelphia startups and a data-center host in funding and event coverage. Ask whether they have an employer or investment relationship with any of the named companies.
IT Pros – Philadelphia
Owned business
Kielinski identifies themself as the founder of IT Pros – Philadelphia, a local tech community with more than 5,000 members, and uses it to connect candidates and employers in the region.
Kielinski's work is easiest to explore through two recurring formats.
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Start with the numbered diagnostic posts on hidden filters that shape hiring decisions and the five stages of a long tech job search.
They make the case that candidates need to understand how hiring really works, even when the rules are unfair.
Then read the role briefs and local Philadelphia market posts to see how they apply that argument to specific searches, employers, and funding news.
The headline and Boolean-search posts are the most directly reusable for improving a profile or sourcing approach.
Across the formats, the through-line is practical: name the hidden rule or local condition, then give the candidate or employer a concrete next move.
Tech recruitingJob search strategyAI and automation in hiringPhiladelphia tech ecosystemTechnical searchCandidate positioningJob postingsNumbered frameworksTech job seekersTech employersPhiladelphia tech professionals
Ghazi Benothman
Both use LinkedIn to connect technology adoption, talent, and investment signals to practical opportunities.
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Kielinski covers Philadelphia hiring and local companies; Benothman examines Tunisia's AI adoption ranking and a small-ticket program for first-time deep-tech founders.
Benothman's lens is national AI-adoption data and Tunisia/diaspora deep-tech investing. Kielinski's is day-to-day tech recruiting, candidate positioning, and Philadelphia employer reputation.
Both publish numbered, copyable job-search guidance for candidates.
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Edelman's posts focus on questions to ask at the end of an interview and treating the interview as two-way; Kielinski's cover recruiter filters and LinkedIn headlines.
Edelman focuses on interview preparation and candidate empowerment. Kielinski also publishes role briefs and local employer-market commentary.
Both are recruiters who explain why applications fail and how candidates can stand out.
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Mikowski uses a PRISM personality profile and a free assessment; Kielinski uses target mapping, direct outreach, and hidden-filter fixes.
Mikowski's posts center on a personality-assessment product and a chief revenue officer search. Kielinski ranges across technical role briefs, AI hiring, and Philadelphia tech.
The content points to a dual audience: Philadelphia-area tech job seekers and the employers or hiring leaders who recruit them.
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Posts offer job seekers headline formulas, search strategies, layoff recovery advice, and application tactics; others address employers and founders on hard-to-fill technical roles, searches, and local hiring conditions.
For a recruiting firm planning content on tech job-market insights and hiring trends, that dual address is relevant.
Before committing, ask for LinkedIn follower demographics and recent post performance by topic to assess whether the audience matches its target employers, candidates, or both.
Brad Kielinski promotes technical searches for employers, hiring support, outplacement for displaced tech workers, one-to-one job-search coaching, candidate promotion, and Philadelphia tech community events through IT Pros – Philadelphia.
They also promote free workshops and a data-center networking event.
The posts do not specify sponsorship terms, rates, or a brand-content format.
Before pursuing a collaboration on hiring-market insights, ask about deliverables, disclosure, approval rights, exclusivity, audience data, pricing, and the scope and business objective.
A Philadelphia-focused B2B recruiting firm wants a six-post co-branded editorial series and one live workshop for founders and hiring managers at local startups and scale-ups, focused on hiring senior technical talent in a tight market.
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Decision: good fit.
Kielinski publishes employer-side search briefs that specify compensation, stack, must-haves, and disqualifiers, making the requested format a close match.
Local funding and community posts provide Philadelphia market context, and the IT Pros – Philadelphia community offers a natural event and distribution partner.
Their candidate-side filters and search stages also give the series a useful two-sided point of view.
Before signing, request audience demographics and post-performance data, and the underlying report and methodology for any AI hiring statistics.
Keep the collaboration to recruiter observation and local market commentary, not audited hiring data.
When to choose a specialist
An enterprise ATS vendor wants an exclusive paid lead-generation campaign—gated whitepapers, demo CTAs, and performance guarantees—aimed at Fortune 500 HR leaders.
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Decision: poor fit.
T.
Brad Kielinski's posts show no product endorsements or sponsorship inventory; their commercial activity is search, outplacement, one-to-one coaching, candidate promotion, and community events.
They are also skeptical of automated screening, describing the ATS black hole and AI tools that auto-reject candidates.
The posts point to a Philadelphia-area technical and hiring community, not a measured Fortune 500 HR audience; request audience data before considering a campaign.
The no-hire employer list is opinionated and unverified, creating reputational risk for a vendor seeking a safe enterprise lead-generation channel.
A narrower collaboration could work as an independent, critical explainer on how automated screening changes hiring—not as a product promotion or guaranteed lead source.
A worked campaign example
Use the good-fit brief.
Campaign angle: 'The Brief Behind the Hire,' a six-post series plus a 45-minute workshop for Philadelphia-area founders and hiring managers.
Each post opens with one element from Kielinski's public role-brief format—role, compensation band, stack, must-have, or disqualifier—and explains a hiring-market lesson.
Post 1 uses the Zero Trust staff engineer brief to show why explicit disqualifiers (not IT admin, DevOps, or backend API roles) protect hiring teams from wasted screens.
Post 2 uses the mobile platform engineer brief to explain what a $200,000–$230,000 band and platform stack signal to senior candidates.
Post 3 turns the 'unspoken filters' into an employer checklist: Big Tech or consultancy background, pre-seed-only leadership, frequent job changes, manual QA, and employment gaps.
Post 4 maps the five candidate stages—optimism, ATS black hole, interview ghosting, existential pivot, practical enlightenment—and asks where the employer's process loses people.
Post 5 connects a local funding round such as Lula, Voomi, or Ethermed to the roles that follow.
Post 6 is the workshop: they and the recruiting firm review one audience-submitted brief live and rewrite it for clarity.
Call to action: register for the workshop and submit one hard-to-fill role for a confidential brief review; no gated whitepaper.
Guardrails: verify the AI hiring percentages against the cited 2026 AI Engineer Hiring Report and its method before reuse; do not present the no-hire employer claims as verified; disclose co-branding and any paid relationship; keep the content to recruiter observation and local market context.
Choose Daryn Edelman when the collaboration should center on the interview stage: how candidates should question employers, what makes for a strong interview conversation, and how employers can structure interviews to reveal fit.
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The posts offer a ready-made question bank organized by recruiter, job, team, manager, and company vision.
T.
Brad Kielinski's two near-identical posts focus on interview questions, not retained search, Philadelphia funding, community events, or a local employer network.
A local hiring series would need new reporting on hiring trends and employer recruiting practices.
Choose Russell Mikowski when the collaboration needs assessment-led candidate differentiation or an executive-search case.
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One post describes attaching a PRISM personality profile to applications after 500 rejections; the other is a CRO search for a first US hire at a Middle Eastern banking platform. That fits a series on how candidates stand out and how senior revenue roles are scoped.
The posts show no Philadelphia tech-market focus or local community distribution.
One promotes the SureCoach.ai assessment product, so a co-branded series would need clear disclosure.
Ask for local hiring trend evidence before building that into the series.
Choose Ghazi Benothman when the collaboration targets deep-tech founders or investors and AI adoption analysis rather than employer hiring tactics.
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The posts cover Tunisia’s position in the Anthropic Economic Index and a €50,000 small-ticket program for first-time deep-tech founders. That supports a founder-facing series on AI markets and early-stage backing.
Neither post addresses recruiting process, compensation requirements, local Philadelphia hiring, or employer-side content.
One is a program solicitation; the other is index commentary.
Ask about audience fit and commercial availability before proceeding.
Brad Kielinski's 24 public LinkedIn posts cover technical searches, job-search advice, AI hiring, Philadelphia funding news, and local events.
The posts include recurring arguments, practical examples, employer and community relationships, and material useful to general readers.
Publication dates do not appear in these posts, so recency and change over time cannot be assessed.
Several posts cite hiring statistics without linking the underlying report, and a list of Philadelphia employers said to appear on no-hire lists does not show the source lists.
Those claims are presented as Kielinski’s stated views, not independently verified findings.
No long-form articles, video, or transcripts appear here.
