AI engineer

Acceler8 Talent; San Mateo (CA); Hybrid; USD 213,000 - 288,000; Full time

Benefits offered by this job

Equity

Hybrid work

Competitive salary

Job summary

Acceler8 Talent in San Mateo is seeking an AI/ML Engineer to own the intelligence layer behind a production AI agent platform. You will architect multi-step agents, retrieval pipelines, and code-generation components that produce reliable data pipelines for enterprise use.

The role emphasizes evaluation loops, model selection for performance and cost, and end-to-end reliability. This is a hands-on position with ownership of core architectural decisions in a regulated enterprise context.

Qualifications

• 4+ years of software-engineering experience with meaningful AI/ML depth.
• Experience building agents, coding assistants, or generative-AI systems in production.
• Strong Python skills.
• Hands-on experience with RAG, retrieval, code generation, or knowledge systems.

Responsibilities

• Own the intelligence layer behind the product, across agent architecture, retrieval, code generation, evaluation, and production reliability.
• Design multi-step agents for planning, retrieval, generation, and error recovery.
• Build evaluation systems and improvement loops for agent quality.
• Develop RAG pipelines using vector search, knowledge graphs, lineage, and metadata.
• Generate and validate production-grade data transformations.
• Select and adapt models for quality, latency, throughput, and cost.
• Lead production deployment of enterprise AI agents.

Skills

Python

AI/ML depth

Agents / AI assistants

Retrieval (RAG)

Code generation

Tools

Neo4j

AWS

Kubernetes

Databricks

Snowflake

Job description

AI/ML Engineer

Hybrid | San Mateo, CA | 3 days on-site

$250k base + equity

I'm working with a well-funded enterprise AI company building agents that turn natural-language requests into production-ready data pipelines.

These agents must understand complex schemas, retrieve the right business context, generate correct transformations, detect errors, and produce workflows that large regulated enterprises can inspect and deploy. The output is working code and data infrastructure, not simply a response in a chat window.

This role will own the intelligence layer behind the product, with scope across agent architecture, retrieval, code generation, evaluation, and production reliability.

You'll work on problems such as:

• Designing multi-step agents for planning, retrieval, generation, and error recovery
• Building evaluation systems and improvement loops for agent quality
• Developing RAG pipelines using vector search, knowledge graphs, lineage, and metadata
• Generating and validating production-grade data transformations
• Selecting and adapting models for quality, latency, throughput, and cost
• Taking AI systems from promising prototypes into reliable enterprise production

Looking for engineers who have:

• 4+ years of software-engineering experience with meaningful AI/ML depth
• Experience building agents, coding assistants, or generative-AI systems in production
• Strong Python skills
• Hands-on experience with RAG, retrieval, code generation, or knowledge systems

Nice to have:

• Vector-database or knowledge-graph experience, including Neo4j
• Experience with AWS and Kubernetes
• Scala or Go
• Databricks, Snowflake, BigQuery, DuckDB, or Spark experience

This is an opportunity to shape how production AI agents reason over complex enterprise data. You'll have direct ownership of core architectural decisions and work on systems where correctness, observability, and trust matter as much as model capability.