Founding AI Engineer (Agentic AI)
9y relevant experience
EU engineers, ready to place with your US clients
Pre-screened on AI. Remote B2B contracts. View 5 full profiles free — AI score, skills report, interview questions included.
Executive Summary
The candidate is a highly experienced Senior ML/AI Engineer whose technical profile is an exceptionally strong match for the Founding AI Engineer role at AlpacaRelay. Their 13-year career, with the last 6+ years focused on production LLM systems, agentic AI, and RAG pipelines using the exact tools specified in the job description (LangGraph, LangFuse, LangSmith, OpenAI GPT-4, Pinecone, RAGAS), places them well above the minimum bar. Their work across large-scale platforms (Brex, Wysa, Fraud.net) demonstrates production-grade thinking, ownership, and measurable impact. The primary due-diligence flags are the future employment end date requiring immediate clarification, the absence of public code artifacts, and a few missing skills (CrewAI, MCP Servers, Anthropic APIs) that should be probed in interview. If technical screening confirms the resume claims, they represents a top-tier candidate capable of immediately contributing to and shaping AlpacaRelay's technical foundation.
Top Strengths
- ✓13 years of experience with 6+ years in production GenAI and agentic LLM systems — far exceeding the 2-year minimum requirement
- ✓Direct match on core agentic AI stack: LangGraph, LangFuse, LangSmith, OpenAI GPT-4, RAG, vector databases, multi-agent orchestration
- ✓Proven ability to own the full AI product lifecycle from architecture to deployment to observability — exactly what a Founding Engineer must do
- ✓Experience across diverse regulated industries (FinTech, HealthTech, Insurance) demonstrating adaptability and production-grade engineering discipline
- ✓Strong cloud infrastructure experience on AWS with Terraform, Docker, Kubernetes, and GitHub Actions CI/CD pipelines
Key Concerns
- !Employment end date of April 2026 at current employer is a future date — this is either a typo or a factual inconsistency that must be clarified immediately
- !Zero public code presence (no GitHub, no open-source contributions) makes independent technical validation entirely dependent on interview performance
Culture Fit
Growth Potential
High
Salary Estimate
$100,000 - $130,000+
Assessment Reasoning
The candidate is assessed as FIT based on an overall score of 88/100. They satisfies well over 80% of the required and preferred skills, with direct hands-on experience in the core agentic AI stack (LangGraph, LangFuse, LangSmith, LangChain, OpenAI GPT-4, RAG, vector databases, multi-agent orchestration, AWS, Docker, Kubernetes, GitHub Actions, PostgreSQL). Their 13 years of experience and 6+ years specifically in production GenAI systems far exceed the 2-year minimum. Multiple projects demonstrate full-lifecycle AI product ownership — from architecture through deployment and observability — which is the defining requirement for a Founding Engineer. The score is held below 95 due to: (1) an unresolvable LinkedIn profile preventing independent verification, (2) a suspicious future employment end date needing clarification, (3) no public code to assess directly, and (4) gaps in CrewAI, MCP Servers, and Anthropic APIs. None of these are disqualifying; they are screening and interview tasks. The candidate should proceed to a technical interview with focused probes on the flagged areas.
Interview Focus Areas
Code Review
No code example or GitHub profile was submitted, making a direct code quality assessment impossible. The resume narratives suggest strong engineering discipline — TDD, CI/CD rigor, evaluation frameworks — consistent with a senior-level engineer. A technical coding assessment or live system-design interview is strongly recommended before making a final hiring decision.
- +Resume demonstrates code quality awareness through TDD practices at HSBC (90%+ coverage with Pytest) and systematic evaluation frameworks
- +Architecture-level thinking evident in system design descriptions (query-routing agents, knowledge graphs, multi-tenant retrieval)
- -No code sample was provided, preventing any direct assessment of actual coding style, quality, or problem-solving approach
- -No GitHub profile linked, meaning no public code artifacts exist to review as a proxy
Experience Overview
13y total · 9y relevantThe candidate presents a highly compelling 13-year career with the last 6+ years deeply focused on production ML and Generative AI systems, directly overlapping with the role's core requirements. Their project work at Globant (Brex, Wysa) demonstrates exactly the kind of agentic AI, RAG, and LLM-orchestration experience AlpacaRelay is seeking, with measurable outcomes at scale. The future employment date (April 2026) and missing GitHub profile are notable gaps that should be clarified in screening.
Matching Skills
Skills to Verify