Agentic AI Engineer
10 hours ago
Dallas
Senior Agentic AI Engineer Embedded Engineering Engagement We are hiring Senior Agentic AI Engineers to join a high-impact engineering team building the next generation of AI-driven software testing and developer workflows. This is not a traditional ML research or model-training role. We are looking for strong software and systems engineers who know how to build with AI agents: designing agentic workflows, integrating agents into existing engineering systems, managing context effectively, and making AI-driven automation reliable enough for real-world use. The ideal engineer is hands-on, highly autonomous, comfortable navigating a large codebase, and able to take an ambiguous problem from concept through implementation. What You'll Work On You may work across several closely related areas, including: • Agentic workflow integration — Integrating autonomous AI workflows into existing engineering and test infrastructure., • AI-driven test automation — Improving systems that generate, execute, analyze, and maintain automated tests., • Context management — Building systems that provide agents with the right code, history, tools, state, and information at the right time., • Developer-agent tooling — Improving how AI agents interact with repositories, build systems, test infrastructure, and engineering workflows., • Reliability and evaluation — Debugging agent behavior, identifying failure modes, and improving the consistency and usefulness of agent-generated results. Responsibilities • Design, build, and integrate production-oriented agentic AI workflows., • Develop tooling that enables AI agents to interact effectively with large codebases and engineering systems., • Improve automated testing and test-generation workflows using LLMs and coding agents., • Design context-management and retrieval strategies for long-running or complex agent workflows., • Debug failures across agents, tools, builds, tests, and surrounding infrastructure., • Build integrations between agentic systems and existing developer/test platforms., • Evaluate agent output and develop mechanisms to improve reliability and reduce failures or unnecessary human intervention., • Work directly with senior technical stakeholders to turn loosely defined problems into working systems., • Own projects end-to-end and communicate progress, risks, and blockers clearly. What We're Looking For Required • 5+ years of professional software engineering experience, or equivalent demonstrated depth., • Strong Python and/or comparable systems/backend programming experience., • Strong Linux and software-debugging fundamentals., • Experience building or integrating LLM-powered applications, coding agents, or agentic workflows., • Experience with APIs, developer tooling, automation, test infrastructure, CI/CD, or large software systems., • Ability to understand and modify unfamiliar codebases quickly., • Strong engineering judgment around reliability, observability, testing, and maintainability., • Excellent written and verbal communication., • Demonstrated ability to independently drive ambiguous technical work. Particularly Valuable Experience • Claude Code, Claude SDK/API, or similar coding-agent platforms., • Agent orchestration, tool use/function calling, MCP, skills, subagents, or multi-step agent workflows., • Context engineering, context management, retrieval, memory, or prompt/tool architecture., • Automated testing frameworks or AI-generated testing., • Large-scale developer infrastructure or internal engineering platforms., • Android, wearables, AR/VR, or other device-oriented development environments., • CI/CD, build systems, containers, telemetry, or production debugging., • Experience embedding AI capabilities into an established engineering ecosystem rather than building standalone demos. Deep ML, computer vision, and model-training expertise are not required. The Engineer Who Will Thrive Here We are looking for someone who combines strong engineering fundamentals with an AI-native way of working. You should be comfortable receiving a problem rather than a detailed implementation plan, investigating the surrounding system, collaborating with stakeholders, and driving toward a working solution. You communicate proactively, surface blockers early, document important decisions, and maintain visibility while working independently. This is a high-autonomy environment where ownership matters as much as technical ability. Example Problems You might be asked to: • Integrate an autonomous testing agent with an existing test platform., • Improve an agent's ability to understand and navigate a large repository., • Build context-management infrastructure for multi-step agent workflows., • Automate portions of test creation, execution, debugging, or maintenance., • Determine why an agent succeeds on some workflows but fails unpredictably on others., • Design tooling that lets an agent safely interact with existing developer infrastructure., • Reduce the amount of human intervention required to complete complex engineering workflows. Engagement Long-term consulting engagement working directly with engineers at a major technology company. Remote, with substantial collaboration across engineering teams.