AI Agent Orchestration Lead

Role Summary

The AI Agent Orchestration Lead is a senior, hands-on engineering leader responsible for operationalizing AI agents end-to-end across the Software Development Life Cycle (SDLC). Working within established AI frameworks, governance models, Dev Ops platforms, and Enterprise Architecture standards, this role focuses on moving beyond pilots and into repeatable, production-grade capabilities that engineering teams rely on daily.

This role partners closely with Solution Architects, Enterprise Architects, delivery teams, security, and IT leadership to coalesce fragmented efforts, align on standard patterns, and lay a durable foundation for scaled AI-driven SDLC automation. The emphasis is on implementation, adoption, reliability, and outcomes.

Key Responsibilities

• AI Agent Implementation & Operationalization: Design, implement, and operationalize AI agents that automate and augment SDLC activities (intake, planning, development, testing, release validation, documentation, and operational support). Build production-grade workflows using approved platforms and frameworks with clear failure handling and lifecycle management. Implement human-in-the-loop controls, approvals, and audit mechanisms.
• SDLC Toolchain Integration: Embed AI agents directly into existing Dev Ops and delivery tools, including backlog management, CI/CD, testing frameworks, ITSM, observability, and knowledge platforms. Ensure agent outputs are actionable and traceable across downstream SDLC stages.
• Governance & Architectural Alignment: Operate within Enterprise Architecture guardrails and embed responsible AI practices, compliance controls, and auditability directly into agent design. Partner with security, risk, and platform teams to ensure AI agents can be monitored and supported like any other production platform capability.
• Adoption & Continuous Improvement: Identify high-value SDLC automation opportunities. Drive real adoption across delivery teams, moving them from experimenting with AI to relying on it. Measure and communicate improvements in cycle time, quality, stability, and developer experience using existing telemetry.
• Enablement & Leadership: Act as a hands-on technical partner and force multiplier for delivery teams by providing reference implementations, playbooks, and guidance. Align stakeholders across architecture, security, and delivery to reduce friction. Provide executive-ready updates focused on operational progress, risks, and outcomes.

Qualifications

Required

• Experience: 8+ years of experience in software engineering, Dev Ops, platform engineering, or solutions architecture, with a strong bias toward delivery and operations.
• Automation Expertise: Demonstrated experience operationalizing SDLC automation on enterprise platforms (beyond just piloting tools).
• AI Production: Hands-on experience implementing governed AI solutions in production environments.
• Leadership: Proven ability to coalesce teams, align approaches, and drive standardization without heavy formal authority.
• Communication: Strong communication skills with the ability to translate technical capability into delivery outcomes.

Preferred

• Education: Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• AI Scale: Experience designing or operating AI agents and agent orchestration frameworks at scale.
• Governance Familiarity: Familiarity with mature AI governance, responsible AI practices, and audit requirements.
• Mindset: Strong execution-oriented engineering mindset with platform and operational thinking.

Measures of Success

• Operational adoption of AI agents across delivery teams using approved, repeatable patterns.
• AI agents functioning as a normal, trusted part of the SDLC rather than isolated pilots.
• Demonstrated improvements in delivery speed, quality, and stability.
• Sustained compliance with architecture, security, and AI governance standards.

Compensation / Pay Rate (Up to): $80.00 - $90.00