About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Computer Hardware Manufacturing.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

This is a hands-on, technical contract role building agentic AI systems and production LLM tooling. You will design, implement, and scale services that power AI agents and LLM-based applications, collaborate with cross-functional teams to take features from prototype to production, and optimize globally distributed systems for performance and reliability.

• Architect and implement agentic AI components using modern LLM libraries and agent frameworks.
• Develop backend services in Python for model orchestration, prompt management, retrieval, and state handling.
• Integrate and tune LangChain, LangGraph, LangFuse, AutoGen (and similar) workflows to enable multi-step agent behavior.
• Build and maintain deployment pipelines and containerized services with Docker and Kubernetes.
• Work with databases (MongoDB, vector stores, and graph databases) to support retrieval-augmented generation and agent memory.
• Optimize systems for latency, throughput, and cost at scale; profile and tune distributed services.
• Collaborate with frontend and full-stack engineers (React, Node/Bun) to ship end-to-end features when needed.
• Write clear documentation, tests, and runbooks to ensure operational readiness for production systems.

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What We’re Looking For

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related discipline — or equivalent experience.
• 5+ years of industry experience building production software (APIs, microservices, distributed systems).
• Strong Python skills and proven experience with application service development and deployment.
• Demonstrable experience or strong projects in AI agent development and agentic workflows.
• Proficiency with agentic LLM libraries/technologies (LangChain, LangGraph, LangFuse, AutoGen, MCP, etc.).
• Experience with databases relevant to AI (MongoDB, vector DBs, graph DBs) and retrieval systems.
• Hands-on experience with Docker and Kubernetes for production deployments.
• Strong problem-solving skills and a track record of taking products from concept to launch and scale.

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Nice-to-Haves

• Experience with performance tuning of large-scale, globally distributed systems.
• Familiarity with frontend stacks (React) and server-side JavaScript runtimes (Node, Bun).
• Prior work on retrieval-augmented generation (RAG), embeddings pipelines, or custom vector search.
• Open-source contributions or public projects demonstrating agentic LLM work.

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Contract Details & Compensation

• Employment type: CONTRACTOR (12-month engagement).
• Location: San Jose, CA (onsite or hybrid per client needs — see interview details).
• Pay: $75–$80 per hour.
• You will be employed by our client (Confidential Client) as a contractor and may receive additional information about benefits or contracting terms during the interview/offer stage.

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Other Important Notes

This posting is written to follow applicable US hiring requirements and non-discrimination practices. Candidates will be evaluated based on skills, experience, and ability to perform the job responsibilities described above.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.