Agile Program Manager (AI Platform)

2026-172982- Senior Manager APM
Duration: 5/12/2027
Location: Boston- 4 days on-site at client office
Interview Process: 3 rounds (1 round will be with client).
Updated job description to help:
Agile Program Manager (AI Platform)
Overview
We are seeking a hands-on Program Leader to drive delivery of our Enterprise AI Platform and the agent portfolio running on it. The role sits at the intersection of AI engineering, platform governance, and AI-augmented delivery.
Key Responsibilities
Agile Program Manager (AI Platform)
Overview
We are seeking a hands-on Program Leader to drive delivery of our Enterprise AI Platform and the agent portfolio running on it. The role sits at the intersection of AI engineering, platform governance, and AI-augmented delivery.
Key Responsibilities

• Own the roadmap, release train, and delivery cadence for a multi-pod AI platform spanning agent runtime, tooling, identity, observability, and enterprise integration.
• Manage dependencies across platform, security, infrastructure, and consuming product teams, and hold the train to a predictable cadence.
• Run the intake funnel for agent use cases: qualify candidates on business value, data readiness, and risk, then convert accepted cases into scoped, sequenced backlog items with clear acceptance criteria.
• Design and operate the gate model that moves an agent from prototype to production, covering evaluation results against curated golden sets, prompt-injection and red-team findings, identity and secrets posture, observability coverage, and a proven rollback path.
• Serve as the primary interface for business sponsors, security, architecture, and platform consumers, translating enterprise constraints into delivery decisions and engineering trade-offs into sponsor-ready language.
• Define the guardrails, human-in-the-loop checkpoints, and audit evidence that keep agentic solutions reliable, explainable, and compliant.
• Drive platform adoption by product teams and report the measures that matter: agent adoption, evaluation pass rates, incident and defect trends, intake-to-production cycle time, and cost per workload.

Required Qualifications

• 8+ years in program, product, or delivery management, including ownership of complex, multi-team technical programs in an enterprise environment.
• Proven command of scaled agile delivery: planning increments, cross-team dependency management, and predictable release cadence.
• Working understanding of how AI agents are built and operated, including LLM behavior, retrieval-augmented generation, tool calling, orchestration, and why evaluation and guardrails are engineering work rather than afterthoughts.
• Technical practitioner skills sufficient to validate outcomes independently: proficiency in SQL and comfort reading telemetry, logs, or evaluation output.
• Demonstrated use of AI tools (Claude, ChatGPT, or similar) to raise personal and team throughput, such as drafting specifications, automating documentation, or analyzing delivery data.
• Familiarity with Azure delivery environments and enterprise controls: identity, network boundaries, secrets management, and change approval.

Preferred Qualifications

• Hands-on or strategic familiarity with Azure AI Foundry and Microsoft Fabric as the delivery stack.
• Exposure to evaluation harnesses, golden-set curation, red-teaming, or responsible AI review as formal release gates.
• Experience partnering with platform operations on SLOs, incident management, and on-call readiness for production services.
• Financial services or other regulated-industry delivery, with the documentation and audit expectations that come with it.

Ideal Candidate
A self-directed leader and agile practitioner who does not wait for assignments, identifies bottlenecks early, and uses every tool available to clear them. Holds a bias for precision, on the conviction that the better the requirement, or the prompt, the better the outcome, whether delivered by an engineer or an agent. Closes gates on evidence rather than assertion, supplies the judgment and context that make AI-accelerated work trustworthy, and brings the client presence needed for high-engagement collaboration and fast feedback loops.