Founding AI Engineer

Jobtailor; Amsterdam; On-site; EUR 120,000 - 180,000; Full time

Job summary

Jobtailor is seeking a senior software engineer to design and own LLM infrastructure, routing across multiple frontier providers, and building eval harnesses that ground AI recommendations in real pricing outcomes.

You will ensure EU data residency compliance, extend MCP servers for programmatic control, and develop observability to surface trust signals for human reviewers, while communicating complex concepts to non-technical stakeholders.

Qualifications

• 8+ years of software engineering experience with strong, recent production LLM depth.
• Shipping and owning LLM-powered features in production.
• Built evals and observability for LLM systems.
• Proficient in TypeScript/Python, FastAPI, GCP, and modern LLM tooling.
• Excellent communicator to explain non-deterministic concepts to non-technical stakeholders.

Responsibilities

• Design and build eval harnesses and benchmarks that use tracked pricing outcomes as ground truth for AI recommendations.
• Own LLM infrastructure and model routing across multiple frontier providers with explicit cost/latency/quality tradeoffs.
• Maintain EU data-residency boundaries for EU customer model calls, ensuring compliance with applicable data regulations.
• Extend an MCP server so LLM agents — including customers' own agents — can programmatically drive the platform.
• Build observability and feedback loops that surface where the AI earns or loses trust from human reviewers.
• Bridge non-deterministic engineering concepts clearly to less technical stakeholders (sales, customer success, leadership).

Skills

LLM Infrastructure Ownership

Production LLM Depth

Eval Harness Development

Full Stack Development

Strong Communication Skills

Tools

GCP

Modern LLM Tooling

Job description

• Design and build eval harnesses and benchmarks that use tracked pricing outcomes as ground truth for AI recommendations.
• Own LLM infrastructure and model routing across multiple frontier providers (Anthropic, Google) with explicit cost/latency/quality tradeoffs.
• Maintain EU data-residency boundaries for EU customer model calls, ensuring compliance with applicable data regulations.
• Extend an MCP server so LLM agents — including customers' own agents — can programmatically drive the platform.
• Build observability and feedback loops that surface where the AI earns or loses trust from human reviewers.
• Bridge non-deterministic engineering concepts clearly to less technical stakeholders (sales, customer success, leadership).

Requirements

• 8+ years of software engineering experience with strong, recent production LLM depth.
• Demonstrated track record of shipping and owning LLM-powered product features in production — not research-only work.
• Has personally built evals and observability for LLM systems (not just consumed someone else's dashboard).
• Comfortable operating across the full stack: TypeScript/Python, FastAPI, GCP, and modern LLM tooling.
• Strong communicator who can make non-deterministic engineering concepts legible to non-technical stakeholders.

Core Competencies

Demonstrates extensive experience in building and maintaining LLM infrastructure, ensuring compliance with data regulations, and effectively communicating complex engineering concepts to non-technical stakeholders. Proficient in full-stack development with a focus on LLM systems and observability.

Highest-signal resume keywords

• LLM Infrastructure Ownership
• Production LLM Depth
• Eval Harness Development
• Full Stack Development
• Strong Communication Skills

ATS Optimization Keywords

Hard Skills

• Software Engineering
• LLM Development
• Eval Development
• Observability
• TypeScript
• Python
• FastAPI

Soft Skills

• Strong Communicator
• Stakeholder Engagement

Industry Keywords

• Data Residency Compliance
• AI Recommendations
• Cost/Latency/Quality Tradeoffs

Tools & Technologies

• GCP
• Modern LLM Tooling