Applied AI Developer
Location: Palo Alto, CA
Schedule: Hybrid
Contract: 3-month contract with potential extension
Compensation: $56.33/hr W2
About the Role:
We are seeking an experienced Applied AI Developer to build and scale production-ready AI solutions and agentic systems. This role will focus on developing AI agents, orchestration frameworks, enterprise integrations, evaluation systems, and governance practices while partnering with engineering, product, security, and business teams.
Key Responsibilities:
- Design, build, and scale agentic and multi-agent AI systems.
- Develop agent orchestration, reasoning, memory, tool integrations, and human-in-the-loop workflows.
- Build automated AI evaluations, simulations, and regression testing frameworks.
- Develop and integrate MCP (Model Context Protocol) solutions.
- Create AI governance patterns, guardrails, auditability, and responsible AI practices.
- Build pilots and proofs-of-concept and transition successful solutions into production.
- Integrate AI solutions with enterprise APIs, databases, and cloud environments.
- Collaborate across engineering, product, security, operations, and business teams.
- Ensure solutions are scalable, reliable, secure, performant, and cost-efficient.
Education & Experience:
- 5+ years of professional software engineering experience required.
- 2+ years of experience focused on applied AI within production systems required.
- Education requirements were not specified in the job description.
Required Skills & Qualifications:
- Strong hands-on Python and/or Go development experience, with the ability to work in both.
- Proven production experience building multi-agent or agent-driven AI systems.
- Experience with modern agent frameworks such as LangGraph, Google ADK, Mastra, or Claude Agent SDK.
- Experience with MCP, AI/LLM orchestration, and leading AI SDKs such as OpenAI or Anthropic.
- Strong backend and systems architecture experience.
- Experience with AWS and/or GCP cloud environments.
- Experience with REST and/or GraphQL APIs.
- Knowledge of authentication and authorization including OAuth2, SAML, API keys, and RBAC.
- Experience with SQL and NoSQL databases.
- Strong communication and cross-functional collaboration skills.
Preferred Skills & Qualifications:
- AI evaluation/observability tools such as Langfuse, LangSmith, or Braintrust.
- Experience building custom MCP servers.
- Docker and Kubernetes experience.
- RAG (Retrieval-Augmented Generation) and document retrieval pipelines.
- Vector databases, embeddings, chunking strategies, and hybrid search.
- AI governance, guardrails, data lineage, and auditability.
- AI inference/cost optimization experience.
- Experience with AI development tools such as Claude Code, GitHub Copilot, Cursor, or Windsurf.
- Ability to work independently in fast-moving, ambiguous environments and take projects from concept through production.
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