• Build and support AI agents and orchestrators on an agentic AI platform powered by Semantic Kernel • Develop and integrate MCP servers and tools using Python FastMCP (core responsibility) • Implement multi-agent workflows (sequential, parallel, and handoffs) with guidance from senior engineers • Design and iterate on prompts and prompt strategies to improve quality and reliability • Contribute to building and maintaining LLM evaluation (eval) pipelines • Integrate LLM providers via APIs/SDKs and support experimentation • Help build RAG pipelines using vector stores and retrieval frameworks • Instrument systems using observability tools like Langfuse for tracing and cost monitoring • Write clean, testable, and maintainable Python code • Participate in code reviews, debugging, and testing • Support CI/CD and deployment workflows • Continuously learn and apply best practices in agentic AI development

• Develop and maintain system features, ensuring code quality and tests; • Contribute to architecture and technical solution decisions; • Work across the full development lifecycle, including deployment and production support; • Operate in an agile environment, collaborating with the engineering team.

• Design, develop, test, and evaluate complex software systems for enterprise‑level business and security applications. • Develop full‑stack technology solutions, including user interfaces and backend services supporting AI‑driven workflows. • Review and approve modifications to existing databases and database management systems. • Direct development of logical and physical database descriptions; ensure proper identifiers and schema definitions. • Approve project scopes, limitations, and technical approaches for database‑related projects. • Plan and implement security measures to protect data against unauthorized access, modification, or disclosure. • Approve, schedule, and supervise installation and testing of new systems, upgrades, and enhancements. • Develop standards, guidelines, and best practices for software acquisition, usage, and information protection. • Estimate time and cost for project requests and system enhancements. • Troubleshoot complex issues and implement system modifications as required. • Provide mentorship, technical guidance, and constructive feedback to team members. • Work independently while managing projects, priorities, and deliverables.

• Automate everything, including scaling, monitoring, and operations. • Build tools to enable self-service both within the team and across all of Chime engineering. • Design, build, and support Chime's cloud infrastructure using automation and infrastructure-as-code. • Develop tools and processes to enable the security, scalability, and availability of the products serving Chime's customers. • Partner with product development engineers to build services according to modern design patterns; for example, the 12 Factor App methodology. • Develop strong relationships with engineers, managers, and other colleagues based on trust, empathy, and technical expertise.