What You’ll Do
Build, own, and continuously improve the AI harness - the frameworks, prompts, context pipelines, guardrails, and evaluation systems that let teams reliably delegate work to AI software development agents
Design and operate agent delivery swarms, orchestrating multiple AI agents to execute complex build and modernization tasks in parallel with strong review, safety, and quality controls
Act as a force multiplier for engineering teams embedding with them to accelerate delivery, unblock hard technical problems, and raise the ceiling of what AI-accelerated teams can produce
Set technical direction and best practices for AI-native software delivery, and drive adoption of these patterns across multiple teams and products
Provide technical mentorship and dotted-line leadership to junior engineers growing their skills in AI tooling, agent orchestration, and modern engineering practices
Own architecture and design for AI-accelerated delivery systems partnering with central architecture teams on cross-cutting changes while retaining decision authority for the AI harness and agent tooling
Establish evaluation, observability, and quality gates for AI-produced code ensuring agent output meets standards for correctness, security, reliability, and maintainability
Integrate AI capabilities with CI/CD pipelines so agent-generated work flows through automated build, test, and safe-release processes (canary, blue/green, phased rollout)
Leverage the enterprise data lake and platform services to ground agents in real context, power AI-driven features, and maximize reuse over rebuilding
Drive both greenfield and modernization work through AI acceleration, sequencing where agent swarms deliver the most leverage and de-risking legacy change
Evaluate and adopt emerging AI tools, models, and techniques prototyping rapidly and bringing proven approaches into production practice
What You’ll Bring
8+ years of hands-on software engineering experience with a track record of operating at a principal / staff+ technical level as an individual contributor
Bachelor's or Master's degree in Computer Science, Engineering, or a related field or equivalent practical experience
Deep, current expertise building with AI development agents and agentic tooling designing AI harnesses, prompt/context pipelines, evaluation frameworks, and multi-agent orchestration ("swarms")
Elite hands-on engineering skills across the full delivery lifecycle, with the ability to build tools and frameworks that other engineers adopt
Strong architecture and system design skills able to own architectural decisions and partner effectively with central architecture teams
Deep expertise in CI/CD and safe delivery practices (automated testing, canary, blue/green, phased rollouts, observability, secure delivery)
Experience with platform / shared-services approaches and data lake / data platform capabilities, and a strong bias for reuse and leverage
Proven ability to act as a force multiplier mentoring engineers, influencing without authority, and driving adoption of new practices across teams
Excellent technical communication and collaboration skills able to align diverse teams on AI-native delivery approaches
A rapid-experimentation mindset staying current with emerging models/tools and translating them into production-grade practice responsibly
It is impossible to list every requirement for, or responsibility of, any position. Similarly, we cannot identify all the skills a position may require since job responsibilities and the Company’s needs may change over time. Therefore, the above job description is not comprehensive or exhaustive. The Company reserves the right to adjust, add to or eliminate any aspect of the above description. The Company also retains the right to require all employees to undertake additional or different job responsibilities when necessary to meet business needs.
