Primary responsibilities
Architecture and technical leadership
Lead design reviews, and drive technical decisions on scalability, reliability, and maintainability.
Translate product requirements into clean, well-tested implementations; author architecture decision records (ADRs) and developer documentation.
Define and govern engineering quality standards, coding conventions, and peer review norms across the team.
AI-assisted and agentic development
AI-assisted development: Leverage GitHub Copilot, Claude Code, and comparable agentic coding assistants across code authoring, review, test generation, and documentation to increase quality and velocity.
AI agent development: Design, build, and maintain AI agents and multi-agent workflows; define agent instructions, skills, memory, and tool integrations; evaluate agent behavior in production.
MCP and tool integrations: Apply Model Context Protocol (MCP) or equivalent patterns to connect AI models to internal tools, APIs, and data sources for agentic workflows.
Stay current with the agentic AI landscape; bring forward-looking proposals to the engineering team.
Full-stack development and collaboration
Build high-quality client-side and server-side code using modern frameworks; design RESTful APIs (OpenAPI standard); develop microservices on Azure or AWS.
Write and execute comprehensive unit and integration test cases; troubleshoot deployment and environment issues across multiple projects.
Mentor engineers, lead code reviews, and contribute actively to sprint ceremonies in a globally distributed Agile team.
Required qualifications
Core
Bachelor’s in computer science or related field (or equivalent experience); 6+ years of progressive software development experience on a commercial product.
Strong CS fundamentals: data structures, algorithms, system design, and distributed computing.
Production-quality C# (.NET); React or comparable front-end framework; NUnit/xUnit testing; Git/Azure DevOps source control.
Relational database experience (PostgreSQL, MySQL, SQL Server) with query optimization; RESTful API design; Agile/Scrum methodology.
Demonstrated experience with performance engineering, scalability design, and observability practices (logging, metrics, distributed tracing) in production systems.
Hands-on experience with AWS services including Lambda, ECS, RDS, API Gateway, CloudWatch, and related cloud-native tooling.
AI and agentic development tools
Hands-on use of GitHub Copilot, Claude Code, or Cursor to write, refactor, and review production code; ability to craft effective prompts and system instructions.
Solid understanding of AI agents, skills, and tool-calling; ability to configure and evaluate agentic workflows for multi-step development tasks.
Working knowledge of an LLM API or agent orchestration framework (Anthropic API, OpenAI API, LangChain, Semantic Kernel, or similar) is a strong plus.
Preferred qualifications
HTML5, CSS, JavaScript/TypeScript with React or Next.js; cloud-native development on Azure or AWS; Docker and Kubernetes.
TDD/BDD methodologies; AI observability tooling; familiarity with the Microsoft development ecosystem.
