Founding AI Engineer (Agentic AI)
5y 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 qualified candidate whose technical profile maps almost precisely to AlpacaRelay's requirements for a Founding AI Engineer. Their current role at Globant is building the same type of agentic, multimodal content generation system that AlpacaRelay is targeting, making them one of the strongest possible profile matches for this position. With 10 years of engineering experience, clear ownership of production AI systems, and demonstrated mentorship capability, they have the seniority and breadth the founding role demands. The primary risks are the absence of verifiable public code artifacts and a significant timezone gap between Krakow and Boston. These concerns are manageable with a structured technical interview and explicit timezone alignment discussions. They are strongly recommended for immediate technical interview progression.
Top Strengths
- ✓Near-perfect technical skill alignment: covers LangGraph, LangSmith, LlamaIndex, RAG, tool calling, OpenAI/Anthropic APIs, AWS, GCP, Kubernetes, Docker, PostgreSQL, GitHub Actions — all core requirements
- ✓Direct domain match: current role involves agentic text-and-image content generation pipelines, exactly what AlpacaRelay is building
- ✓Full-stack ownership mindset demonstrated across prototyping, productionization, deployment, monitoring, mentorship, and incident response
- ✓10 years of engineering experience with progressive responsibility, including founding-engineer-level scope at Globant (owned architecture, CI/CD, evaluation frameworks, and team mentorship)
- ✓Strong quantified impact: 45% latency reduction, 3x throughput increase, 60% reduction in human post-edit time, MTTR reduced from 120 to 40 minutes — shows outcome orientation
Key Concerns
- !No verifiable public code artifacts (no GitHub, no open-source links, no portfolio) — technical depth must be validated through interview process
- !Poland-based candidate (GMT+2) applying to a Boston-based startup (ET, GMT-4/5) — 6-7 hour timezone gap may create friction for tight founder collaboration in an early-stage environment
Culture Fit
Growth Potential
High
Salary Estimate
$80,000 - $110,000 USD (within posted range; Poland-based candidates may have lower expectations but role is senior-level with founding equity upside)
Assessment Reasoning
The candidate is assessed as FIT with a score of 88/100. They meets or exceeds all minimum requirements and matches approximately 95% of the required skill set with explicit production evidence. Their current role at Globant — building agentic LLM-powered text-and-image content pipelines using LangGraph, LangSmith, LlamaIndex, RAG, tool calling, AWS, Kubernetes, and GitHub Actions — is a near-identical technical context to AlpacaRelay's stated product direction. They clears the 80%+ required skills threshold comfortably. The experience level (10 years total, 5 years in AI/LLM systems) is appropriate for a senior founding engineer. No major red flags are present; the two concerns (no public code artifacts, timezone gap) are verifiable and manageable risks rather than disqualifying factors. The score is held below 90 primarily due to the absence of a code sample and inaccessible LinkedIn profile, which prevent full independent verification. A technical interview is strongly recommended to confirm coding quality before offer, but on the basis of the application as presented, this candidate should be advanced.
Interview Focus Areas
Code Review
No code example or GitHub profile was submitted, so direct code quality assessment cannot be performed. However, the resume narrative describes mature engineering practices including TDD, modular architecture, prompt-layer decoupling, and automated evaluation harnesses, which are consistent with senior-level output quality. A technical interview or take-home assessment should be used to validate hands-on coding ability before proceeding to offer.
- +Resume descriptions demonstrate strong engineering discipline: TDD, CI/CD, modular prompt layers, evaluation harnesses
- +Evidence of production-grade thinking: structured outputs, rollback procedures, hallucination scoring dashboards
- -No code sample or GitHub profile was provided, making direct code quality assessment impossible
- -Open-source contributions mentioned as a hobby but no links or repositories shared — reduces confidence in hands-on verification
Experience Overview
10y total · 5y relevantThe candidate presents an exceptionally well-matched resume for this role, covering nearly every required and preferred technical skill with direct production evidence. Their current role at Globant is strikingly aligned with AlpacaRelay's content generation use case, including LLM agent orchestration, multimodal pipelines, RAG, and cloud deployment. With 10 years of total engineering experience and a clear 5-year trajectory into AI/LLM systems, they sits comfortably at the senior level this role demands.
Matching Skills
Skills to Verify