AI/ML Engineer

About the role

We're partnering with a well-funded, high-growth Series B startup building the next generation of AI-native data infrastructure for Fortune 500 enterprises.

Responsibilities

• Architect multi-step AI agents end-to-end, covering problem decomposition, context retrieval, error recovery, and output quality
• Own RAG pipelines, vector and graph-based retrieval systems, and knowledge representations that let agents reason accurately over complex enterprise data
• Build the AI layer behind the platform's core code generation capability, from prompt design and model selection through to fine-tuning and output validation
• Make production AI work at scale, balancing latency, throughput, and observability, and know when to optimize a model versus restructure a system
• Think in failure modes and evaluation strategy, not capability demos, and own the improvement loop

Requirements

• 4-6+ years of software engineering experience with meaningful AI/ML depth
• Proven experience building and shipping AI agents or coding agents in production
• Strong Python skills with hands-on experience across RAG, vector databases, and knowledge graphs
• Experience with LLM APIs, prompt engineering, fine-tuning, and structured outputs in production
• Familiarity with AWS and Kubernetes for production AI deployment
• Experience with data platforms such as Databricks, Snowflake, BigQuery, or Spark is a strong bonus
• Scale or Go experience is a bonus

Qualifications

If you're a builder who thinks in failure modes, owns what you ship, and thrives in environments where last year's best practice is already obsolete, this is a rare opportunity to have direct leverage on a product used by some of the world's largest enterprises.