AI/ML Engineer

Harnham; San Francisco (CA); Presencial; USD 180.000 - 280.000; Jornada completa

Descripción de la vacante

Harnham is seeking a senior AI/ML software engineer to own the intelligence layer of an AI-native data platform for enterprise clients. You will architect multi-step agents, design RAG pipelines, and drive production-grade AI features from model selection to output validation.

Ideal candidates have 4–6+ years of software engineering with deep AI/ML experience, strong Python skills, and hands-on work with LLMs, vector databases, and knowledge graphs.

Formación

• 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.

Responsabilidades

• 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 knowing when to optimize a model versus restructure a system.
• Think in failure modes and evaluation strategy, not capability demos, and own the improvement loop.

Conocimientos

Python

AI/ML depth

AI agents in production

LLM APIs

Prompt engineering

AWS

Kubernetes

Herramientas

Databricks

Snowflake

BigQuery

Spark

Descripción del empleo

We're partnered with a well-funded, high-growth Series B startup building the next generation of AI-native data infrastructure for Fortune 500 enterprises. With 3.5x revenue growth in FY'24 and 160% net revenue retention, they're scaling fast and investing heavily in the AI engineering team that powers their core product.

This is a high-impact role where you'll own the intelligence layer of the platform, making real architectural decisions around agent design, model selection, and evaluation strategy. Everything you build ships directly to customers; this is not a POC or internal tooling team.

What You'll Do

• 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 knowing 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

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.