Experience:

• 5+ years of professional software engineering
• At least 2 years focused on applied AI in production systems

Responsibilities:

• Evaluate where AI fits and build practical AI tools and platforms
• Prototype, evaluate emerging AI technologies, and ship solutions
• Build automated evaluations, simulation tests, and regression frameworks
• Design agentic systems including tool orchestration, agent reasoning, memory, MCP integrations, and human-in-the-loop workflows
• Define and implement AI governance patterns including guardrails, data lineage, auditability, and responsible AI practices
• Drive adoption through pilots, proofs-of-concept, and scalable implementations
• Collaborate with business functions, product, security, and platform teams to deliver production-grade AI solutions

Additional responsibilities:

• Maintain quality bar for AI systems to ensure reliability and scalability
• Handle infrastructure, performance, failure modes, cost, and deployment concerns
• Design scalable, reliable backend systems
• Work with backend databases including writing queries and building data access layers enforcing role-based access control
• Partner cross-functionally with Product, Operations, and domain experts
• Raise standards for clarity of thinking, system design, and team execution

Nice to have:

• Experience with AI evaluation tooling such as Langfuse, LangSmith, Braintrust, or custom eval frameworks
• Experience building custom MCP servers
• Familiarity with containerization and orchestration using Docker and Kubernetes
• AI-native builder with intellectual curiosity and rapid adoption of new tools
• Hands-on experience with inference cost optimization
• Experience using AI-powered coding agents like Claude Code, GitHub Copilot, Cursor, Windsurf
• Experience with RAG architectures and document retrieval pipelines including vector databases, embedding models, chunking strategies, and hybrid search

More skills:

Python, Go, multi-agent or agent-driven systems, Braintrust, MCP implementations, OpenAI SDK, Anthropic SDK, systems and backend architecture, cloud-native environments, GCP, AWS, enterprise APIs, REST, GraphQL, OAuth2, SAML, API keys, RBAC, SQL, NoSQL