Chris Walker | Partner - AI Talent

Founder - AI Talent @ CW
Helping AI firms hire people who actually make their product work in the real world
NYC • London • Global | Open roles + market intel

[Chris Walker | Partner - AI Talent @chrispwalker]

2026 Enterprise AI Hiring Snapshot (NYC + London)

Forward-Deployed Engineers: $200K–$250K base
Solutions Engineers: $170K–$200K base

What actually wins offers right now:
→ Customer-facing deployment speed
→ Ownership mindset over pure comp
→ Tight 2-week interview loops

Just placed 3 in the last 30 days.

Hiring? Candidate? DM me, I keep shortlists ready.

[Chris Walker | Partner - AI Talent @chrispwalker]

FDE is going vertical

The next wave of FDE hiring isn’t about frameworks. It’s about domains.

Look at what’s live right now:

OpenAI hiring an FDE for legal, embedding with law firms
Together AI hiring an FDE in post-training
Thomson Reuters hiring a CoCounsel FDE
Lovable hiring an FDE Lead across NYC and Stockholm

In finance, postings mentioning “agent orchestration” are up 1,721% this year (Draup via CNBC). The FDEs banks want need two things: engineering depth and real knowledge of how a trading desk or compliance team works.

Here’s what that means if you’re an engineer.

Your LangGraph experience isn’t the moat. Everyone will have it in six months.

Knowing how a contract review actually flows through a law firm, or how a credit committee makes a decision - that’s the moat. It’s hard to learn, and it compounds.

The engineers I’m seeing get multiple offers right now pair production AI work with one industry they understand deeply.

What’s your domain? If you’ve built in legal, fintech, healthcare or insurance, I’d like to hear from you - DM me.

[Chris Walker | Partner - AI Talent @chrispwalker]

Founding Engineer @ a $20M AI-native supply chain company (backed by Kleiner Perkins).

You'll own entire problem domains end-to-end, talk to customers, and shape engineering culture from day one.

SF on-site. $150K–$300K + founding-level equity. DM if you're a builder who ships. 🚀

#FoundingEngineer #AI #SupplyChain #SFJobs #StartupJobs #Hiring

[Chris Walker | Partner - AI Talent @chrispwalker]

Hiring: Full-Stack Product Engineers, NYC

AI-native medical practice. a16z + GV backed, 5x revenue this year, Fortune 10 go-live.

TypeScript, React, Node, Postgres, AWS. 0-to-1 builders only.

$190K-$225K + equity. 3-4 days in Flatiron. ~2-week process.

DMs open. #hiring #NYCtech

[Chris Walker | Partner - AI Talent @chrispwalker]

I’m looking for experienced independent recruiters or established recruitment teams to support a live software engineering hiring project on a commission-only basis.

You should have:
• Access to strong software engineering talent in UK/US
• Proven sourcing and candidate qualification experience
• The capacity to work quickly and independently
• Clear, reliable communication

CW Resourcing will provide the role brief, hiring criteria and ongoing support. An agreed fee split will be paid for every successful placement.

Interested? Email me at [email protected] with a brief introduction and details of your recruitment experience or team.
PLEASE NOTE: ONLY CONTACT VIA EMAIL WILL BE RESPONDED TO.

[Chris Walker | Partner - AI Talent @chrispwalker]

@verycracked Some great opportunities here.

[Chris Walker | Partner - AI Talent @chrispwalker]

Hiring: AI Product Engineer - SF (hybrid)

Series A AI company deploying bespoke AI into Fortune 100s across gov, insurance + healthcare. ~150 people, ~90% engineers.

Want: 0-to-1 builders. Real product sense. TypeScript or Python. Customer-facing.

$150-300k base + equity.

Founder-type energy? DM me.

[Chris Walker | Partner - AI Talent @chrispwalker]

This is the real split. The premium isn't on who can train a model, it's on who can walk into legacy systems, compliance blockers and sceptical ops teams and still ship something that survives. That's a judgment and ownership profile, not a stack. Also why it's so hard to hire: it barely shows up on a CV.

[Chris Walker | Partner - AI Talent @chrispwalker]

Fair critique, and true for the FDEs sold by the hour. The ones who compound value are different: they feed every deployment back into the product so the next one needs less hand-holding. A bodyshop scales headcount; a real FDE function shrinks the gap between demo and production. Same title, opposite economics.

[Chris Walker | Partner - AI Talent @chrispwalker]

@gregisenberg The "$1M in 30 days" headline will pull the wrong crowd, but the core is right: the scarce skill isn't the code, it's business reality + judgment + building in one person. Which is also why most FDE hires miss, companies screen hard for the third and ignore the first two.

[Chris Walker | Partner - AI Talent @chrispwalker]

Agreed, closest thing to a paid founder apprenticeship in tech. Customer exposure, product ownership and shipping under pressure, all at once. Which is exactly why the best FDEs are a flight risk to go start something. If you're hiring them, the retention question matters as much as the sourcing one.

[Chris Walker | Partner - AI Talent @chrispwalker]

Means so many jobs it now means nothing" is exactly right — and it's a hiring problem, not just semantics. When the title spans pre-sales SE to founding product engineer, candidates and companies talk past each other for three interviews. The fix is boring: define the actual outcome the person owns before you write the JD

[Chris Walker | Partner - AI Talent @chrispwalker]

This is the whole case for the FDE role in one stat. The model was never the bottleneck — proprietary data, regulated workflows and sceptical users are. That's a human-in-the-customer's-environment problem, which is exactly why every serious lab is now hiring for it instead of shipping more demos.

[Chris Walker | Partner - AI Talent @chrispwalker]

Hottest, and the hardest to hire for. "Build AI + talk to clients + ship fast + solve real business problems" is four different people in most talent pools. The rare ones who are all four don't stay on the market long — they get pulled into founding roles. Speed of process matters more here than almost any other hire.

[Chris Walker | Partner - AI Talent @chrispwalker]

Palantir productised it, but the DNA is older - embed someone who owns the outcome inside the customer's environment. What's new is that AI finally made it a mainstream role instead of a Palantir quirk. The hiring bar hasn't moved though: ownership and customer judgment first, stack second.

[Chris Walker | Partner - AI Talent @chrispwalker]

@mehdig Exactly — the role isn't new, the label is. Anyone dropped into a customer's environment to make new tech actually land has done this job. Good news for hiring: the best FDEs are often sitting in forward-deployed field and solutions roles that predate the title entirely.

[Chris Walker | Partner - AI Talent @chrispwalker]

This is the line that matters: demo is easy, daily-trusted product is hard. The engineers who cross that gap, reliability, evals, sitting with the users who'll actually adopt it — are the scarce hire right now. Most "AI Product Engineer" JDs still screen for the demo skill and then wonder why adoption stalls.

[Chris Walker | Partner - AI Talent @chrispwalker]

Never too late. Simplest version: an FDE is an engineer who sits inside the customer's world, works out their actual problem, and ships the thing that solves it, then feeds what they learned back into the product. Less "build to spec", more "own whether it works in the real world."

[Chris Walker | Partner - AI Talent @chrispwalker]

Take full ownership as a founder engineer of another company's product is the best one-line definition I've seen. And you're right that depth isn't the bar — I've watched brilliant engineers fail as FDEs because they couldn't read a room, and average-on-paper ones thrive because they own outcomes. Screen for ownership and customer instinct, not LeetCode.

[Chris Walker | Partner - AI Talent @chrispwalker]

Love this take,@startupideaspod. Treating support tickets as direct engineering input could be transformative for retention and product-market fit. The tricky part is doing it without burning out the engineering team. Have you seen any startups build sustainable systems or rituals around this ‘support → prototype → ship’ loop?

[Chris Walker | Partner - AI Talent @chrispwalker]

This is such a good framing,@oceancurve. ‘Customer-back engineering’ feels like the antidote to building cool tech that nobody actually needs. I’ve seen teams where engineers regularly join customer calls or support rotations and the impact on relevance is huge. The Capital One example sounds powerful — have you come across other companies doing this well at scale?