Lead Application Development Engineer

cloud software group•San Ramon, CA

2d•$145,351 - $248,551

About The Position

The Lead Application Development Engineer – Agentic Engineering will join the AIX (AI for Engineering Excellence) team to design, build, and operationalize AI-powered agents and agentic workflows across the Software Development Life Cycle (SDLC). This role will drive scalable, secure, governed, and production-ready AI engineering solutions that improve developer productivity, software quality, and engineering automation across Cloud Software Group.

Requirements

AI-powered agents and agentic workflows across the Software Development Life Cycle (SDLC)
Scalable, secure, governed, and production-ready AI engineering solutions
Improve developer productivity, software quality, and engineering automation
Design and develop AI agents and agentic engineering workflows for software development, testing, code review, issue resolution, and engineering operations.
Build multi-agent orchestration solutions that enable agents to plan, execute, validate, and collaborate on complex engineering tasks.
Integrate AI agents with enterprise engineering platforms including GitHub, Jira, CI/CD pipelines, source repositories, testing systems, and developer tools.
Develop reusable agents, skills, tools, APIs, MCP servers, and agent-to-agent integrations.
Research and evaluate emerging LLMs, coding agents, agent frameworks, and AI engineering technologies.
Establish production patterns for agent governance, security, observability, evaluation, guardrails, and human-in-the-loop controls.
Develop prototypes and PoCs and transition successful solutions into scalable production services.
Partner with engineering organizations to identify SDLC processes that can be transformed into agent-driven workflows.
Provide technical leadership, architecture guidance, code reviews, and mentoring to engineering teams.

Responsibilities

Design and develop AI agents and agentic engineering workflows for software development, testing, code review, issue resolution, and engineering operations.
Build multi-agent orchestration solutions that enable agents to plan, execute, validate, and collaborate on complex engineering tasks.
Integrate AI agents with enterprise engineering platforms including GitHub, Jira, CI/CD pipelines, source repositories, testing systems, and developer tools.
Develop reusable agents, skills, tools, APIs, MCP servers, and agent-to-agent integrations.
Research and evaluate emerging LLMs, coding agents, agent frameworks, and AI engineering technologies.
Establish production patterns for agent governance, security, observability, evaluation, guardrails, and human-in-the-loop controls.
Develop prototypes and PoCs and transition successful solutions into scalable production services.
Partner with engineering organizations to identify SDLC processes that can be transformed into agent-driven workflows.
Provide technical leadership, architecture guidance, code reviews, and mentoring to engineering teams.