Job Type: Contract
Contract Length: Ongoing
Pay Range: $75 - $80/hr
Start Date: ASAP
Location: Hybrid - Palo Alto, CA
About the Opportunity:
Our client, a leader in Enterprise AI and Distributed Systems, is looking for a skilled AI Developer to join their team for an ongoing engagement. This project involves evaluating where AI can make a real difference, building the platforms and patterns that make adoption easy, and enabling engineering teams to work smarter and faster through modern AI development patterns. This is a high-impact role that requires a self-motivated professional who can hit the ground running and deliver results quickly.
Key Responsibilities & Deliverables:
This role is focused on the successful completion of specific tasks and deliverables. Your responsibilities will include:
- System Design: Designing agentic systems including tool orchestration, agent reasoning, memory, MCP integrations, and human-in-the-loop workflows.
- Quality Assurance: Building automated evals, simulation tests, and regression frameworks that ensure AI systems are reliable and improving as they scale.
- Governance: Defining and implementing AI governance patterns—guardrails, data lineage, auditability, and responsible AI practices.
- Adoption & Implementation: Driving adoption through pilots, proofs-of-concept, and scalable implementations across engineering teams.
- Cross-Functional Collaboration: Collaborating with various business functions, product, security, and platform teams to translate AI use cases into production-grade, end-to-end solutions.
We are looking for someone with a proven track record of successful contract engagements. The ideal candidate will have:
- Experience: 5+ years of professional software engineering, with at least 2 years focused on applied AI in production systems.
- Deep Expertise: Proven experience building and scaling multi-agent or agent-driven systems in production. This isn't a learning role—you need to be a subject matter expert.
- Technical Proficiency: Proficient in Python and/or Go; strong systems and backend architecture fundamentals (scalable, reliable systems, failure modes, cost).
- Agent Ecosystems: Hands-on experience with modern agent ecosystems, including frameworks (e.g., LangGraph, Google ADK) and observability/evals tooling (e.g., Langfuse, LangSmith, Braintrust).
- Architecture: Good understanding of cloud-native environments (GCP and/or AWS) and experience designing and integrating with enterprise APIs (REST, GraphQL) and backend databases (SQL and NoSQL).
- Collaboration: Strong cross-functional collaborator and communicator, able to partner with Product, Operations, and domain experts to deliver end-to-end systems.
- W2 only (No C2C or 1099 contractors)





