Agentic Engineering Lead

Vantor•Westminster, CO

About The Position

Vantor is seeking an Agentic Engineering Lead to transform how Engineering operates through AI, automation, and agentic software development. This role will establish the technical direction and build the agentic capabilities that enable our Engineering Operating Model. You will also partner with engineering teams to adapt and adopt the Agentic Software Development Lifecycle based on their unique products, architectures, missions, and engineering constraints.

Requirements

Experience consistent with a Vantor T7/Principal technical leader: typically 15+ years with a bachelor’s, 10+ with a master’s, 8+ with a PhD, or equivalent experience.
Deep software engineering and architecture expertise, including modern SDLC, automation, APIs, developer tooling, and systems integration.
Hands-on experience designing and building AI agents, agentic systems, or AI-enabled engineering workflows.
Strong understanding of LLMs, context engineering, orchestration, evaluation, observability, guardrails, and human-in-the-loop patterns.
Demonstrated ability to establish technical direction and influence senior engineers, architects, and engineering leaders across an organization.
Must be a U.S. Person, defined as a U.S. citizen, permanent resident, Asylee, or Refugee.

Nice To Haves

Experience deploying production-grade agentic or autonomous engineering systems.
Experience integrating AI with engineering systems such as GitHub, Jira, CI/CD, documentation, and observability platforms.
Experience driving adoption of new engineering practices across diverse teams.
Experience in aerospace, defense, mission-critical, or other high-assurance engineering environments.

Responsibilities

Architect and build agentic workflows across the software development lifecycle and Engineering Operations.
Translate engineering standards, playbooks, governance, and systems of record into automated workflows, controls, and agents.
Implement the Engineering data architecture and systems-of-record model, including the integrations, context, and traceability required to support agentic workflows and trusted engineering data.
Define scalable patterns for agent architecture, context, human/agent handoffs, guardrails, evaluation, and observability.
Advise engineering teams on adapting and adopting the Agentic SDLC for their specific architectures, workflows, risks, and mission requirements.
Develop reusable agentic capabilities and patterns that can scale across Engineering.
Measure the adoption and effectiveness of agentic engineering capabilities and continuously improve them.