Founding AI Engineer (Agentic AI)
4y 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 an experienced Senior LLM/GenAI Engineer with a strong foundation in production RAG systems, enterprise AI platforms, and LLM evaluation — areas directly relevant to AlpacaRelay's mission. Their 7-year track record includes demonstrable cost savings and platform scale at credible employers. However, they falls short on several role-critical requirements: modern agentic AI frameworks (LangGraph, CrewAI, LlamaIndex, MCP), AWS/GCP cloud experience, and a visible public technical presence. For a founding engineer role demanding cutting-edge agentic AI expertise and startup-speed execution, these gaps create meaningful risk. They are best classified as BORDERLINE — a strong RAG/LLM generalist who may lack the specific agentic AI depth this role demands, but whose transferable skills and engineering maturity make their worth a technical interview to validate.
Top Strengths
- ✓7+ years of production AI/ML experience with measurable enterprise impact
- ✓Deep expertise in RAG architectures, LLM evaluation, and enterprise-grade AI platform design
- ✓Proven track record at credible organizations (Wipro, UNICC, SGS & Co)
- ✓Experience with multimodal AI systems and conversational AI products
- ✓Strong understanding of AI observability, evaluation frameworks, and feedback loops
Key Concerns
- !Lacks explicit experience with core agentic AI frameworks required for this role (LangGraph, CrewAI, LlamaIndex, MCP Servers)
- !No public code presence, GitHub profile, or open-source work submitted — critical gap for a founding engineer role
Culture Fit
Growth Potential
Moderate
Salary Estimate
$80,000 - $100,000 USD (aligns with stated range given India-based location on B2B remote contract)
Assessment Reasoning
The candidate meets approximately 55-60% of the required skills and experience criteria. Their strengths in RAG, LLM integration, production AI deployment, and enterprise platform design are genuinely relevant and impressive. However, the role's core requirement — hands-on experience with modern agentic AI frameworks like LangGraph, LangSmith, LangFuse, CrewAI, LlamaIndex, and MCP Servers — is conspicuously absent from their resume. These are not peripheral nice-to-haves; they are central to the Founding AI Engineer (Agentic AI) title and day-to-day responsibilities. Additionally, the lack of AWS/GCP experience, no GitHub or public code presence, and absence of a cover letter or code sample all reduce confidence in their fit for this specific early-stage, agentic-AI-first role. They do not cross the threshold for FIT but has enough relevant depth to warrant a structured technical interview to determine if they have undocumented agentic AI experience or can credibly bridge the gap rapidly. Classified as BORDERLINE pending HR and technical review.
Interview Focus Areas
Code Review
No code example or GitHub profile was submitted, making a direct code quality assessment impossible. Based on resume context alone, the candidate appears to have senior-level systems design experience, but the lack of any publicly verifiable code is a meaningful gap for a founding engineer position that demands hands-on technical credibility.
- +Resume demonstrates systems-level thinking through architecture design of RAG pipelines and multi-tenant platforms
- +Use of evaluation frameworks (DeepEval) suggests structured, quality-oriented engineering approach
- -No code sample, GitHub profile, or open-source contributions were provided — cannot directly assess code quality
- -Absence of public code presence is a concern for a founding engineer role requiring demonstrable technical depth
Experience Overview
7y total · 4y relevantThe candidate presents a strong profile as a Senior LLM/GenAI Engineer with 7+ years of experience and clear production impact in RAG, NLP, and enterprise AI platforms. However, their resume lacks direct evidence of modern agentic AI frameworks (LangGraph, CrewAI, LlamaIndex, MCP) which are central to this role. Their Azure-centric background and absence of AWS/GCP experience may also limit fit for a startup likely operating on multi-cloud infrastructure.
Matching Skills
Skills to Verify