For a startup hiring AI agent and LLM engineers between Seed and Series C, Recruiting from Scratch is the strongest fit: it recruits only engineers, works on contingency with no upfront cost, and half its candidates reach an offer within 29 days of their first interview. We've placed an agent software engineer in New York at Decagon. For a Head of AI, retained search is the better choice.
Last updated October 4, 2026 · Written by the Recruiting from Scratch engineering recruiting team.
Hiring engineers who have shipped agents in production? Recruiting from Scratch sends 3–5 qualified engineers, on contingency. Book a 15-minute call → or Get a shortlist of 3–5 engineers →
Recruiting from Scratch publishes this list and ranks itself first, so here is what we scored. Five criteria, weighted by what founders building agents raise:
We rank ourselves first on depth and stage fit, and say where others fit better.
| # | Firm | Best for | Stages | Roles | Model |
|---|---|---|---|---|---|
| 1 | Recruiting from Scratch | Agent and LLM software engineers | Seed to Series C | Agent, LLM, ML, forward-deployed, backend | Contingency, replacement guarantee |
| 2 | Riviera Partners | AI and engineering leadership | Venture-backed, seed to late stage | VP Eng, Head of AI | Retained search |
| 3 | Paraform | Posting a role to independent recruiters | Seed to growth | Most technical roles | Marketplace of recruiters |
| 4 | Hunt Club | Senior hires via referrals | Venture-backed and growth | Senior and leadership roles | Search fee |
| 5 | Dover | Founders running their own process | Pre-seed to Series A | Any role you source yourself | Software plus optional services |
| 6 | Builder-community networks | Engineers active in agent open source | Any | Hackers and early contributors | Communities and meetups |
Best for: startups building agents, copilots and LLM-powered products who need engineers with production experience.
Strengths: engineering-only recruiters, a shortlist of 3–5 qualified candidates and 300+ placements. We've placed an agent software engineer in New York at Decagon, machine-learning engineers at Mercor and forward-deployed engineers at Cinder.
Limitations: engineering only. We don't place research scientists or run C-suite search, and the agent talent pool is young, so expect to flex on years of experience.
Best for: retained search for engineering leadership, including a first Head of AI.
Limitations: not designed for several individual-contributor hires.
Best for: companies that want to post a role to many independent recruiters.
Limitations: agent expertise varies by recruiter.
Best for: senior hires through a referral network.
Limitations: less suited to volume engineering hiring.
Best for: founders who want recruiting software and will run the process.
Limitations: the founder still sells, screens and closes.
Best for: engineers who build agents in public, through open-source projects, hackathons and meetups.
Limitations: informal, slow and not scalable.
An agent engineer is a software engineer first. They build systems where a model plans, calls tools, reads and writes state, and recovers from failure. Day to day that means tool and API design, retrieval, evaluation harnesses, latency and cost control, guardrails and observability. The best ones can say what broke in the last agent they shipped and how they measured the fix.
That makes them hard to find. The title is new, so resumes say everything from "AI engineer" to "full-stack." Tutorials produce plenty of demo builders and few people who have kept an agent reliable under real traffic. Look for evaluation experience, production incidents and opinions on when not to use an agent. Our guide on hiring an LLM engineer breaks the profiles apart, the forward-deployed engineers guide covers the customer-facing variant, and AI engineers at Series C startups covers later stage. Compare compensation with Carta's data.
Be clear on the profile first. For a product engineer who builds agent features, a contingency engineering firm works. For a researcher training models, use advisor referrals. For a leader, use retained search. Teams hiring in New York can read our New York AI and ML startup guide.
Recruiting from Scratch, for agent, LLM and ML software engineers from Seed to Series C: contingency pricing and 300+ placements, with half of candidates reaching an offer within 29 days of a first interview.
Production experience with tool calling, evaluation and failure handling. A demo is easy; keeping an agent reliable is the skill.
Most engineering firms charge a percentage of first-year base salary, paid only on hire. Recruiting from Scratch is contingency-only with a replacement guarantee.
Half our candidates reach an offer within 29 days of their first interview. The pool is young, so decisions made quickly win candidates.
Not always. Many strong ones are backend or full-stack engineers who learned evaluation. Research roles are different.
Related: Best Recruiting Firms for AI Startups Hiring ML Engineers · Best Recruiting Firms for Forward-Deployed Engineers in New York · Best Recruiting Firms for Legal Tech Startups
Recruiting from Scratch sends a shortlist of 3–5 agent and LLM engineers who fit your stack, stage and budget, on contingency with a replacement guarantee.
Get a shortlist of 3–5 engineers → or Book a 15-minute call →
Looking for a role building agents instead? See the engineering roles we're hiring for now →
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