AI/ML Engineer

Harnham; California; Ibrido; USD 315.000 - 385.000; Tempo pieno

Descrizione del lavoro

Harnham is seeking an AI/ML Engineer (All Levels) in the San Francisco Bay Area with hybrid work options. The role focuses on architecting and deploying multi-step AI agents, RAG pipelines, and knowledge representations in a production environment.

You will work on code generation features, model selection, and evaluation strategies that scale for enterprise data. Ideal candidates have 4–6+ years of software engineering with AI/ML depth, strong Python skills, and hands-on experience with LLM

Competenze

• 4-6+ years software engineering with AI/ML depth
• Proven experience shipping AI agents in production
• Strong Python and data infra experience (RAG, vector DBs, KG)

Mansioni

• Architect multi-step AI agents end-to-end
• Own RAG pipelines, vector retrieval, knowledge representations
• Build AI layer behind core code generation capability
• Ensure production AI operates at scale (latency, throughput, observability)
• Think in failure modes and evaluation loops

Conoscenze

Python

AI/ML depth

LLM APIs

RAG pipelines

Vector databases

Prompt engineering

AWS

Kubernetes

Go/Scale experience

Strumenti

Databricks

Snowflake

BigQuery

Spark

Descrizione del lavoro

Title: AI/ML Engineer (All Levels)

Location: Bay Area (Hybrid)

Compensation: Up to $350,000 + Equity

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.