AI-Powered Candidate Sourcing Tool

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Not a one-shot search. An AI sourcing agent that learns and improves with each cycle.

Each cycle refines its queries based on where the best candidates came from. You can steer it at any point.

Intake

Asks calibration questions to understand what good really looks like

Search

Maps the ecosystem and runs targeted queries from multiple angles

Score

Evaluates every profile against your criteria with transparent reasons

Learn

Analyses where the best candidates came from and refines its approach

Repeat until shortlist is complete

A real completed AI sourcing search for a Forward Deployed Engineer role — 54 candidates found, scored against hiring criteria, and ranked in minutes. Candidate details have been redacted for privacy.Scroll through the conversation to see the agent’s reasoning, then explore the shortlist.

Forward Deployed Engineer, Applied AI

My read on this role before I start searching:

  • The hardest intersection to find: Someone who can write production Python and run enterprise customer discovery and has hands-on LLM/agent development experience — not advisory familiarity. This eliminates most SEs (too sales-adjacent) and most ML engineers (not customer-facing).
  • Two very different talent pools both qualify: Current FDEs/SEs at AI platform companies (Terrace Data, Acumen AI, AWS Bedrock, Ridge Computing AI) vs. technical founders who built AI products and now want to operate in enterprise contexts. These require completely different search strategies.
  • The founding FDE framing matters: Anthropic explicitly says this person "helps shape the forward-deployed motion" — suggesting they want someone who can build the playbook, not just follow one. That points toward more senior, independent operators.
Primary Archetype

Which candidate archetype should I prioritise — and this will shape roughly 60% of my search direction?

AI platform FDE/SE
Technical AI founder
AI consultancy engineer

All three are great actually. I'd say 2 is highest prio since they are usually customer facing people and good at product dev. and 3 is lowest prio

Domain Weighting

The JD lists financial services and healthcare as 'a plus' — how much should I weight enterprise vertical experience in practice?

Deprioritise it — LLM depth is the filter
Weight FS or healthcare backgrounds
Weight any complex enterprise context

Broader than FS/healthcare — anyone who's deployed LLMs inside large, complex organisations (government, manufacturing, legal, etc.) gets the same credit.

Geography

Anthropic is headquartered in San Francisco with the JD listing location as unknown. Should I search globally or focus geographically?

US-wide (SF + NYC + remote-eligible)
SF / Bay Area first

Prioritise Bay Area candidates given the likely hybrid expectation, then expand if the pool is thin. Tighter but more outreach-ready.

Global search

Got it — technical founders first, then AI platform practitioners, with AI consultancy engineers as a lower priority. Bay Area-focused, and any complex enterprise context (not just FS/healthcare) counts as a plus. Let me map the ecosystem and start searching.

Refined role brief
Researched companies15 results
Researched companies12 results

Good ecosystem map. I can see key companies to target across archetypes — now launching parallel searches.

Searched candidates15 profiles
Searched candidates15 profiles
Searched candidates15 profiles

Good results across all three searches. Triaging now and scoring the most promising profiles.

Evaluated candidates23 scored

Exceptional initial yield — all three queries are performing very well. Adding strong candidates to the shortlist and reinvesting in the highest-performing directions simultaneously.

Added to shortlist+21 (21 total)
Searched candidates17 profiles
Searched candidates6 profiles

Triaging the new batch and expanding from top-scoring candidates simultaneously.

Evaluated candidates9 scored
Expanded search50 profiles

8 out of 9 scoring at 8+ — the founder-CTO angle is delivering exceptional results. Adding to shortlist and scoring the most promising candidates from the similarity expansion.

Added to shortlist+9 (30 total)
Evaluated candidates20 scored
Planned next steps
continue

An outstanding result — one perfect score has emerged from this round. Adding new candidates and running a second expansion pass with the freshest top performers as seeds.

Added to shortlist+17 (47 total)
Expanded search50 profiles
Searched candidates15 profiles

We're at 47 candidates and just 3 away from the initial target. Scoring the strongest new profiles from the similarity expansion to close out this round.

Evaluated candidates7 scored
Planned next steps

Adding the final batch to hit our target, then wrapping up with a full checkpoint.

Added to shortlist+7 (54 total)
Refined role brief

The strongest candidates in this pool are SF-based technical founders who are currently building enterprise AI products at tiny startups — they're often one good conversation away from considering a founding FDE role at Anthropic.

Shortlist Summary — Forward Deployed Engineer, Applied AI · Anthropic

54 candidates total | 37 scoring 8+ | 17 scoring 7


🟢 Tier 1 — Highest Outreach Priority (founders/between roles/most likely receptive)

These candidates are currently running very early-stage ventures or just transitioned — they have the right skills and the timing is good.

NameCurrent StatusScoreWhy They Stand Out
Devon SalemCo-Founder, Circuit Logic10The standout of the entire pool. Explicitly builds RAG/multi-agent platforms with Pulse Automation, Quantum Solutions, Claude, and GPT in production for enterprise clients (manufacturing, healthcare, finance). SF Bay Area, consulting shop means he's likely open. Screen for: MCP server experience, availability.
Morgan MishraFounder FDE, Beacon AI (Aug 2025)9Literally gives himself the title "Forward Deployed Engineer" in his own startup. Lists MCP, RLHF, multi-agent, RAG. Ex-Spark Innovation, Crest Solutions (fintech), Fanatics. The homecoming angle is compelling.
Avery ParundekarFounder + Principal MLOps, Circuit Logic9SF-based, 17 years ML/MLOps. Infrastructure Architect at Quantum Solutions, member of technical staff at Apex Software AI, now consulting at Circuit Logic. The customer-embedding consulting model he already lives is close to FDE. Screen for: agent/MCP depth, Python confirmation.
Val MoinFounder, Xero Tech (Sep 2025)9Just left Prism Analytics after 6 years leading Azure GenAI customer deployments — this is peak receptivity. Has Python/TF/PyTorch, healthcare AI founder background. Perfect outreach timing.
Skyler Amine BellajdelFounder stealth (Oct 2025)9Most recent ex-Apex Software (LLM evaluation company) Customer Solutions Engineer Lead. Before that, senior engineer at Ridge Computing. Hands-on RAG eval work cutting inference from 5s to 200ms using Claude/Pulse Automation/Python. SF Bay Area.
Winter AminSenior AI Architect, Prism Analytics9Currently running Prism Analytics's enterprise AI Transformation Program — literally architecting and deploying Azure AI Foundry + RAG/agents/Python for strategic enterprise customers. The parallels to this FDE role are direct. Ex-Horizon Tech, ex-Circuit Logic Principal AI Architect.
Rowan BrandtCEO, Vanguard Tech (2-person startup)9Production LLM agents, RAG pipelines, nationwide voice deployments, HIPAA-compliant healthcare builds. ARC-AGI 2 lead contributor — signals genuine frontier engagement. Very likely open to a well-framed Anthropic pitch.
Sage ReccoCEO, Spinf (early stage)9VP Engineering at Zeal Computing for 6 years (built APIs for NBC, Disney, Nexus Software, Ridge Computing at enterprise scale), now building real-time AI sales agents. Python, Hugging Face, TensorFlow listed. Classic "big company technical leader turned founder" who'd thrive as an FDE.

🔵 Tier 2 — The Broader Pool (46 candidates)

AI platform practitioners (Terrace Data, Acumen AI, AWS): ~12 candidates including Riley Stoneman (Staff SA, Acumen AI; ex-AWS; Boston), Casey Field (SA Terrace Data, London), Kit Oksar (GTM Engineer, Terrace Data), Finley Martin (Solutions, Acumen AI/Nexus Software), Hunter Hamiti (Manager GenAI SA, AWS). Strong technical signals but currently at direct competitors — outreach needs a compelling mission narrative. Note: Casey Field and Oakley McMeechan are EMEA-based; viable if Anthropic has flexibility there.

FDE practitioners (Palantir, Vertex AI, Beacon AI): Dakota Marin (AI FDE Beacon AI, ex-Palantir Technical Lead — one of the cleanest title matches), Parker Jeong and Lane Arbaugh (Vertex AI FDEs — good enterprise AI deployment reps), Quinn Stallings (Senior FDE at Atlas Digital, just started December 2025). These candidates have the exact title but the LLM/agent depth is less verified than the founders.

Bay Area AI founders at growing startups: Morgan Agarwal (Horizon Tech), Jordan Avtomonov (Catalyst Engineering, YC X25), Sydney Shahani (Core Digital, YC W23), Ellis Murga (Catalyst Engineering, ex-Forge Data Head of AI), Spencer Huang (multi-agent builder, ex-Vanguard Tech/Flux Labs/Element Systems), Grey Majee (25+ enterprise customers for GenAI security). Higher bar to move since their startups have more momentum, but mission-driven outreach can work.

Enterprise AI veterans making transitions: Tatum Vohra (ex-Beacon AI Staff Applied Research Scientist building enterprise LLMs/RLHF, now founding stealth), Ashton Burke (Head of Applied AI at Vector Logic, ex-Beacon AI/Nexus Software AGI), Marley Nivargi (Founder CTO Astra Networks, post-Beacon AI acquisition).


What I Learned

The founder archetype over-delivers. Every query targeting AI startup founders yielded 89-100% at 7+. The signal is strong — but many of these founders are running tiny shops because they prefer agency and ownership. Outreach framing matters enormously: position this as Anthropic's founding FDE role with influence over the entire playbook, not a standard engineering hire.

Python is the invisible screen. Only about 40% of otherwise strong candidates explicitly list Python on Element Systems. It's the single most important first-call question — many profiles imply it through role context (Pulse Automation, FastAPI, SageMaker) but don't state it. Don't let a clean profile fool you.

MCP / agent depth is a differentiator. There's a clear divide between candidates who build RAG/chatbot pipelines (2022-era skills) and candidates who are working with MCP servers, agentic orchestration frameworks, and evaluation pipelines (2024-era). The latter group is much smaller. Devon Salem, Morgan Mishra, and Frankie Chheda stand out on this dimension.

Bay Area is dense with this talent. The majority of top-scoring candidates are currently in SF or the broader Bay Area — which is rare for a role this specialized. Limited location friction for the priority outreach list.


Take a look through the shortlist and let me know what you think of the candidates. I can go deeper on any archetype, run a second pass focused specifically on Hugging Face/developer-advocate backgrounds, or pivot toward any direction that's missing from what you're seeing.

What recruiters say about AI-powered sourcing

11 or 12 very good calls booked in for strong-looking candidates, and I've already sent one across. The results are clearly there.

AlexHead of Talent, Energy Sector

Manual sourcing for this kind of search is a nightmare. Nova just handed me a shortlist I'd have spent a week building myself.

CallumTalent Lead, Staffing

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