10 Best AI Engineer Job Boards in 2026

The AI engineer market changed in 2025. By 2026, the question is no longer "where do I post an AI role" but "where do I find engineers who have actually shipped LLM apps, RAG pipelines, agent frameworks, and production inference workloads instead of just listing them on a resume." Generalist job boards have not caught up. Most still treat "AI engineer" as a synonym for "data scientist" or "ML researcher," which it is not.

The hard part is filtering. Every board claims AI talent. Few have the volume, the verification, or the specialization to deliver candidates who can actually build with the Claude Agent SDK, LangGraph, vector databases, or modern multi-agent orchestration. Salary ranges swing wildly between regions and seniority tiers, and many of the loudest platforms are paid-acquisition layers over the same LinkedIn pool. Specificity matters more than reach.

This guide compares the 10 best AI engineer job boards in 2026. Real coverage, honest pricing where it is publicly available, pros and cons, and a framework to pick the right board for your role, your budget, and your hiring timeline.

Best AI engineer job boards: a brief overview

• Wellfound (AngelList Talent): Best for startup and seed-to-Series-B AI roles with equity-heavy comp.
• LinkedIn AI Jobs: Best for volume and passive-candidate reach across every seniority tier.
• Hugging Face Jobs: Best for ML researchers, model builders, and open-source AI contributors.
• Anthropic Careers: Best as a benchmark for top-tier safety and frontier AI roles.
• AI Jobs Board (ai-jobs.net): Best free, no-noise vertical board for AI/ML/data roles globally.
• Otta (now Welcome to the Jungle): Best for curated, candidate-first AI roles in Europe and the US.
• Hired: Best for reverse-marketplace AI hiring with salary upfront.
• Y Combinator Work at a Startup: Best for early-stage AI founders hiring engineer #1 through #10.
• Built In AI: Best for US tech-hub AI roles with strong employer branding.
• Toptal AI: Best for vetted freelance and contract AI engineers on demand.

1. Wellfound (AngelList Talent), best for startup AI roles with equity transparency

Wellfound (formerly AngelList Talent) is the default AI engineer job board for venture-backed startups. Roles posted here come with salary ranges, equity grants, and funding-stage context upfront. For AI engineers who want to work on GenAI products at seed-to-Series-B startups, the platform consistently surfaces roles that would never appear on traditional boards.

Key features

• Salary and equity disclosed on every listing
• Founder-to-candidate direct messaging
• Filters for funding stage, remote policy, and tech stack
• Curated "AI / ML" job vertical with thousands of listings

Best for

• Seed-to-Series-B startups hiring AI engineers with equity comp
• Candidates who want startup roles and equity transparency
• Founders who want to message engineers directly without a recruiter layer

Pricing

• Free to post basic jobs for startups
• Paid recruiter tier ("A-List Pro") for outbound sourcing — custom pricing

Pros

• Massive startup density, especially in YC and Tier-1 VC portfolios
• Salary and equity visible upfront kills tire-kicking
• Founder-led messaging shortens time-to-first-interview
• Strong filtering by funding stage and remote policy

Cons

• Skews heavily toward seed-to-Series-B; thin coverage at FAANG-scale or pure research
• Volume in non-US markets is limited compared to LinkedIn

2. LinkedIn AI Jobs, best for volume and passive-candidate reach

LinkedIn remains the largest professional network on the planet, and its AI jobs vertical reflects that scale. Every Fortune 500, big-tech AI lab, and series-C+ startup posts here. The "AI engineer" job category has grown nearly 10x since 2022, and LinkedIn's targeting tools make it the broadest reach available for any AI hiring manager.

Key features

• AI-focused job alerts and recruiter targeting
• Skill assessments for Python, ML, and adjacent stacks
• Recruiter and Recruiter Lite tiers for outbound sourcing
• InMail to passive candidates outside the public job pool

Best for

• Enterprises hiring senior AI engineers and ML leads at scale
• Recruiters running passive-candidate outbound campaigns
• Candidates open to inbound but not actively applying

Pricing

• Single job posts from ~$495 (pay-per-click model)
• LinkedIn Recruiter from ~$9,000 per seat per year
• Recruiter Lite from ~$170 per month

Pros

• Largest passive AI talent pool in the world
• Excellent filtering by seniority, location, and skill
• Strong employer brand surface area through company pages
• Skill assessments add a baseline filter

Cons

• Application volume is high and quality varies widely
• Costs add up fast at scale; not budget-friendly for early-stage startups

3. Hugging Face Jobs, best for ML researchers and open-source talent

Hugging Face is the de facto hub of the open-source AI community. Its job board is small but uniquely positioned: every candidate browsing it is already deep in transformers, datasets, and model deployment. For research-leaning AI engineering roles, model training, or fine-tuning work, no other board has this density.

Key features

• Integrated into the Hugging Face ML community and model hub
• Candidate profiles often include public model and dataset contributions
• Filters for ML research, MLOps, and applied AI
• Direct visibility into candidates' open-source footprint

Best for

• Companies hiring ML researchers and model engineers
• Roles requiring deep transformer, fine-tuning, or inference expertise
• Candidates who already contribute to Hugging Face Spaces, datasets, or models

Pricing

• Free job postings for community-aligned roles
• Premium employer features available on request

Pros

• Best signal-to-noise ratio for research-leaning ML roles
• Candidates often have public, verifiable open-source contributions
• Strong fit for fine-tuning, evaluation, and model deployment roles

Cons

• Lower volume than LinkedIn or Wellfound
• Skews research and ML over applied AI engineering

4. Anthropic Careers, best as a benchmark for frontier AI roles

Anthropic Careers is not a job board in the marketplace sense — it is a single-employer careers page. We include it because it sets the benchmark for what frontier AI roles look like in 2026: detailed scoping, transparent compensation philosophy, and clear separation between research, applied, and engineering tracks. AY Automate is an Anthropic Partner Network member, and Anthropic's hiring bar shapes how serious AI teams structure roles industry-wide.

Key features

• Clear separation: research, applied AI, infrastructure, product engineering
• Detailed role scopes with explicit responsibilities and qualifications
• Public compensation philosophy and seniority levels
• Safety and alignment roles published alongside engineering

Best for

• Candidates benchmarking comp and scope for AI engineer roles
• Hiring managers studying how a frontier lab structures AI hiring
• Researchers targeting safety and alignment tracks

Pricing

• Not applicable — single employer

Pros

• Industry-leading reference for how to scope an AI engineer role
• Transparent compensation and leveling
• Strong signal of what frontier AI work actually entails

Cons

• Not a marketplace — you cannot post jobs here
• Roles are highly competitive; conversion rate is low for most candidates

5. AI Jobs Board (ai-jobs.net), best free vertical board for AI/ML/data

ai-jobs.net is the cleanest vertical AI job board on the open web. No social network noise, no general business listings — just AI, ML, MLOps, and data roles. For employers who want a free or low-cost channel that reaches an AI-specific audience, this is the most efficient option.

Key features

• 100% AI/ML/data vertical
• Free standard job posts
• Paid featured listings for higher visibility
• Salary transparency on most listings

Best for

• Startups and SMBs hiring AI engineers on a budget
• Niche roles where LinkedIn application volume would be overwhelming
• Candidates searching only AI/ML/data without unrelated noise

Pricing

• Free standard job posts
• Featured listings from ~$199 per post

Pros

• Zero noise; every visitor is AI-focused
• Free tier is genuinely useful, not a teaser
• Salary transparency is the norm
• Strong global reach for remote AI roles

Cons

• Smaller passive talent pool than LinkedIn
• Limited employer branding features compared to Built In or Otta

6. Otta (Welcome to the Jungle), best for curated, candidate-first AI roles

Otta — now part of Welcome to the Jungle — built its reputation on candidate-first curation. Each listing is reviewed for clarity, salary transparency, and role quality. For AI engineers in the UK, EU, and parts of the US, it is one of the highest-signal boards available. Employers get fewer but better-qualified applicants.

Key features

• Curated listings reviewed for quality and clarity
• Salary, equity, and tech stack disclosed on every role
• Company culture profiles with mission, perks, and values
• Strong UK and EU coverage; growing US presence

Best for

• Product-led AI startups hiring mid-to-senior engineers
• UK and EU AI roles
• Candidates who prioritize culture and salary transparency

Pricing

• Custom employer subscriptions (typical range $5k–$15k/yr)
• Volume discounts for larger hiring teams

Pros

• Curated listings improve candidate experience and brand
• Salary and equity transparency reduces ghosting
• Strong UK/EU reach with growing US coverage
• Above-average company profile depth

Cons

• Smaller US footprint than LinkedIn or Wellfound
• Curation gatekeeping means slower posting workflow

7. Hired, best for reverse-marketplace AI hiring with salary upfront

Hired flips the model: candidates create profiles, employers reach out with salary offers attached. For mid-to-senior AI engineers tired of one-way application flows, it is a refreshing change. Employers pay a success fee only when a hire is made, which removes upfront posting costs.

Key features

• Reverse-marketplace model — employers reach out to candidates
• Salary expectations and interview requests upfront
• Candidate vetting via interviews, skill checks, and references
• Strong filtering by ML/AI specialization and stack

Best for

• Mid-to-senior AI engineers actively interviewing
• Employers willing to pay a success fee for shorter time-to-hire
• Teams that want salary alignment before the first call

Pricing

• ~15% of first-year base salary (success fee model)
• No upfront posting fees

Pros

• Success-fee pricing aligns incentives
• Salary transparency from the first interaction
• Vetted candidate pool reduces low-quality outreach
• Faster time-to-hire than traditional posting

Cons

• Success fee is expensive at senior salary tiers
• Smaller global reach; strongest in US tech hubs

8. Y Combinator Work at a Startup, best for early-stage AI engineer hires

YC's Work at a Startup is exclusive to Y Combinator companies, which makes it small but high-density. Almost every YC AI startup posts here first. For engineers who want to work on pre-seed-to-Series-A AI products, it is the single best concentrated funnel. Candidate volume per company is high because the YC brand draws talent.

Key features

• Exclusive to YC-backed companies
• Founder-led messaging and applications
• Profile-based candidate matching
• Strong concentration of GenAI and agent startups

Best for

• YC AI startups hiring engineer #1 through #10
• Candidates who want pre-seed-to-Series-A roles
• Engineers seeking founder-led teams with high equity upside

Pricing

• Free for YC companies
• Not available to non-YC employers

Pros

• High concentration of AI-native startups
• Founder-led process speeds up hiring
• Candidate quality skews strong due to YC brand
• Free for YC companies

Cons

• Only YC companies can post — not accessible to outside employers
• Heavy startup-only bias; no enterprise roles

9. Built In AI, best for US tech-hub AI roles with strong employer branding

Built In is a hub-by-hub job board across major US tech cities — NYC, SF, LA, Austin, Chicago, Boston, Seattle, Denver — with a dedicated AI vertical. It pairs job posts with rich employer profiles, including tech stacks, perks, and culture content. For mid-to-senior US AI hiring with employer-brand investment, it is one of the strongest options.

Key features

• Dedicated AI vertical across US tech hubs
• Rich employer profiles, tech stack pages, and culture content
• SEO-optimized for "AI jobs in [city]" search queries
• Audience skews mid-to-senior engineers

Best for

• US-based AI employers investing in employer brand
• Companies hiring mid-to-senior AI engineers in specific cities
• Candidates targeting tech hubs over fully remote roles

Pricing

• Employer subscriptions typically $4,000–$8,000 per year
• Custom pricing for enterprise and recruitment marketing

Pros

• Strong SEO for "AI jobs in [city]" searches
• Rich employer profiles improve conversion
• Mid-to-senior audience density in US tech hubs
• Recruitment marketing tools beyond job posting

Cons

• US-focused; limited international coverage
• Annual subscription model is overkill for one-off hires

10. Toptal AI, best for vetted freelance and contract AI engineers

Toptal's AI vertical specializes in freelance and contract AI engineers, vetted through a multi-stage screening process. For teams that need an AI engineer on a project basis — proof-of-concept, RAG pipeline, agent prototype — without committing to a full-time hire, Toptal is the most mature option. AY Automate complements this for teams that want managed delivery rather than freelance staffing — see our AI agent development service.

Key features

• Multi-stage candidate vetting (under 3% acceptance rate, per Toptal)
• Specialized AI/ML talent pool
• Risk-free trial period on placements
• Hourly, part-time, and full-time contract options

Best for

• Teams needing freelance AI engineers for project work
• Proof-of-concept and prototype builds
• Companies that want vetted talent without an internal screening process

Pricing

• Hourly contract rates typically $80–$200/hr depending on seniority
• No upfront platform fee — pricing baked into hourly rate

Pros

• Strong vetting reduces hiring risk
• Fast time-to-engagement (often within days)
• Flexible engagement models (hourly to full-time contract)
• Risk-free trial period reduces commitment risk

Cons

• Premium hourly rates; not cost-effective for long-term FTE work
• Less suited for permanent senior hires than reverse-marketplace boards

How to choose the best AI engineer job board for your role

1) Are you hiring full-time or contract?

If you need a permanent AI engineer, your shortlist is LinkedIn AI Jobs, Wellfound, Otta, Built In AI, and Hired. LinkedIn and Wellfound give the broadest reach. Otta and Built In win on candidate experience. Hired wins on time-to-hire if you can stomach the success fee. For startup hires with equity comp, Wellfound is the default — see our guide to how to hire AI engineers for full-cycle hiring playbooks.

If you need contract or fractional help, Toptal AI is the most mature vetted marketplace, and managed delivery partners like AY Automate offer a different model — outcomes instead of hours.

2) Are you a startup, a YC company, or an enterprise?

YC companies should post on Work at a Startup first — it is free and high-density. Early-stage non-YC startups should lead with Wellfound plus AI Jobs Board for a free secondary channel. Enterprises should run LinkedIn Recruiter with Built In AI for branded employer presence. Companies hiring research-leaning ML talent should add Hugging Face Jobs.

3) How much can you spend on hiring channels?

Bootstrapped budgets can run AI Jobs Board (free), Hugging Face Jobs (free), and YC Work at a Startup (free if applicable). Mid-budget teams add Wellfound and individual LinkedIn posts. Enterprise budgets unlock LinkedIn Recruiter, Otta, Built In AI, and Hired. Toptal is best treated as a per-project line item, not a hiring channel.

4) How specific is the role?

For frontier research, ML training, and fine-tuning roles, Hugging Face Jobs and Anthropic Careers (as a benchmark) lead. For applied AI engineering — RAG, agents, Claude Agent SDK, LangGraph — Wellfound, LinkedIn, and AI Jobs Board convert best. Before posting anywhere, get the scope right with our AI engineer job description template — vague JDs are the single biggest reason AI roles stay open for six months.

Where AY Automate fits in

AY Automate is not a job board. We are an AI agent development partner for teams that want to ship production agents and automations without spending six months staffing an internal AI team. We build with the Claude Agent SDK, LangGraph, and modern RAG patterns, and we deliver in EN, FR, and AR. If you are stuck between "hire an AI engineer" and "need this shipped in 60 days," talk to us — we'll be honest about whether you should build an internal team, hire freelance, or work with a partner. Book a free consultation and we'll scope it together.

FAQ

What is an AI engineer job board?

An AI engineer job board is a hiring channel focused specifically on AI, ML, and applied AI engineering roles. It differs from general job boards (Indeed, ZipRecruiter) by either being purely vertical (ai-jobs.net, Hugging Face) or by offering AI-specific filtering, vetting, and candidate signals within a larger platform (LinkedIn AI Jobs, Wellfound).

How is an AI engineer job board different from a general tech job board?

General tech boards lump AI engineers in with data scientists, backend engineers, and ML researchers. AI-specific boards separate applied AI engineering (LLM apps, agents, RAG) from research and from data infrastructure, which gives both sides better filtering. They also tend to surface AI-native employers candidates actually want to work for.

How do I verify an AI engineer candidate is legit?

Ask for shipped, production AI work — not just side projects. Verify open-source contributions on GitHub or Hugging Face. Run a paid one-day take-home that mirrors real work: build a small RAG pipeline, ship a Claude Agent SDK prototype, or evaluate a model. Reference checks should focus on outcomes shipped, not titles held.

How much does it cost to hire an AI engineer in 2026?

In the US, mid-level AI engineers run $180,000–$260,000 base, with senior roles at frontier labs clearing $400,000+ all-in. Job board costs are a fraction of total hiring cost: $500 single posts (LinkedIn) to $9k+/yr seats (LinkedIn Recruiter) to 15% success fees (Hired). Toptal contract rates run $80–$200/hr.

How long does it take to hire an AI engineer?

In 2026, average time-to-hire for a mid-senior AI engineer is 8–14 weeks for full-time roles. Reverse marketplaces like Hired compress this to 3–6 weeks. Freelance engagements through Toptal can start within days. Internal references and warm intros from VCs remain the fastest channel of all.

Is a specific certification or badge important for AI engineers?

Less than you'd think. Shipped production work, open-source contributions, and evidence of building with frontier models matter far more than coursework certificates. Anthropic, OpenAI, and Google cloud certifications can be useful tiebreakers for cloud-deployment roles but are not gating credentials at most AI-native employers.

Should I post on LinkedIn or Wellfound first?

If you are a venture-backed startup hiring under Series B, post on Wellfound first — the audience matches and salary/equity transparency works in your favor. If you are an enterprise or a later-stage company hiring at scale, LinkedIn AI Jobs gives you the volume and passive reach you need. Most serious roles end up on both.

Can a job board help train my internal AI team?

Job boards hire — they don't train. If you need to upskill an existing team on Claude Agent SDK, LangGraph, RAG, or agent orchestration, work with a delivery partner who can pair-build with your engineers. AY Automate runs enablement engagements where we ship the first agent alongside your team and leave them with the patterns to ship the next one solo.