AI Engineer

• Python development for LLM-powered applications and AI agents
• Agentic AI systems, including tool orchestration, MCP integrations, and automated LLM evaluations
• Cloud-native backend and API development (REST, GraphQL, OAuth2, RBAC)

What You’ll Do

• Assess where agentic approaches outperform conventional solutions for internal workflows
• Design and build agentic systems covering tool orchestration, agent reasoning, memory, MCP integrations, and human-in-the-loop steps
• Build automated evals, simulation tests, and regression frameworks to keep AI systems reliable as they scale
• Implement AI guardrails, data lineage, auditability, and responsible AI practices
• Prototype and evaluate emerging AI tools and technologies
• Deliver pilots, proofs of concept, and scalable implementations across engineering teams
• Integrate agents with enterprise APIs and SQL/NoSQL databases using role-based access controls
• Partner with product, security, platform, and business teams to take AI use cases to production

• 4+ years of professional software engineering, including 1+ year building LLM-powered applications or agents
• Strong Python skills
• Hands-on experience building agentic workflows with tool calling and a leading LLM SDK such as OpenAI or Anthropic
• Backend fundamentals, including REST or GraphQL APIs, authentication and authorization patterns (OAuth2, SAML, RBAC), and SQL/NoSQL databases
• Working knowledge of a cloud platform (AWS or GCP), including compute, storage, and managed AI services

Preferred / Bonus

• Go (Golang) experience
• Production ownership of multi-agent systems at scale
• Agent frameworks such as LangGraph, Google ADK, Mastra, or the Claude Agent SDK
• Evaluation and observability tooling such as Langfuse, LangSmith, or Braintrust
• Building custom MCP servers
• Docker and Kubernetes
• Inference cost optimization for scaling agent deployments
• AI coding agents such as Claude Code, GitHub Copilot, Cursor, or Windsurf
• RAG architectures, including vector databases, embedding models, chunking, and hybrid search

Our client is a publicly traded data security software company headquartered in Silicon Valley, serving enterprises worldwide with backup, recovery, and cyber resilience solutions.