Partner with engineering teams to identify, design, and improve AI-assisted workflows across coding, testing, review, documentation, and delivery.
Build and refine reusable AI skills, agent workflows, prompts, MCP integrations, and automation patterns that can be shared across the organization.
Evaluate emerging AI development tools (including coding agents and AI-assisted review) and integrate them into an agentic software development lifecycle (SDLC).
Guide the transition of successful experiments into repeatable, secure, observable, and production-ready engineering practices.
Contribute improvements to repositories, tooling, and internal enablement materials to help teams adopt AI-first practices.

Experience using AI-assisted development tools (such as GitHub Copilot, Cursor, Claude Code) in real engineering workflows.
Practical understanding of agentic development concepts, including skills, agents, MCP servers, tool use, and LLM-based workflow automation.
Proficiency in Python, Go, or a similar programming language.
Experience with RHEL or other Linux distributions
Experience with containerization and orchestration using Kubernetes or Red Hat OpenShift.
Ability to evaluate developer workflows, handle high context-switching, and work comfortably in an emerging area with changing requirements.
Solid communication skills to collaborate with engineering teams, understand their constraints, and guide practical technology adoption.
Experience with developer productivity, developer experience, or platform engineering (considered a plus)
Experience with PyTorch, TensorFlow, CUDA, ROCm, GPUs, or AI/ML infrastructure (considered a plus)
Contributions to upstream AI/ML open source communities (considered a plus)
Experience with agile development, test-driven development, CI/CD, or software supply chain practices (considered a plus)

Senior Software Engineer – AI Workflows, SDLC

Key skills