Corporate Vice President - Release Train Engineer (RTE) - Agentic AI Web Application

Location Designation: Hybrid - 3 days per week

Release Train Engineer (RTE) - Agentic AI Web Application Role Overview

We are seeking an experienced Release Train Engineer (RTE) to lead delivery of a next-generation Agentic AI web application. The RTE will serve as the delivery and execution leader across multiple agile teams responsible for building AI-powered user experiences, autonomous/agentic workflows, platform services, integrations, and production capabilities.

This role sits at the intersection of product, engineering, AI/ML, architecture, security, and operations, ensuring teams remain aligned on outcomes while managing the unique delivery risks associated with rapidly evolving generative and agentic AI technologies.

The ideal candidate combines strong SAFe/Agile program leadership with sufficient technical fluency to facilitate discussions involving LLMs, AI agents, APIs, cloud platforms, data, security, observability, and modern web architectures.

Key Responsibilities

Agile Release Train Leadership

• Lead and facilitate the Agile Release Train (ART) across product, web engineering, AI/ML, platform, architecture, security, QA, and DevOps teams.
• Facilitate PI Planning, ART Syncs, Scrum of Scrums, system demos, Inspect & Adapt sessions, and dependency/risk reviews.
• Partner with Product Management and Architecture to translate product strategy into executable PI objectives and delivery plans.
• Maintain visibility into milestones, dependencies, risks, impediments, and cross-team commitments.
• Drive predictable delivery without sacrificing experimentation and learning required for emerging AI capabilities.
• Coach teams and leaders on Agile/SAFe practices and continuously improve ART effectiveness.

Agentic AI Delivery

• Coordinate delivery of capabilities involving LLMs, AI agents, tool/function calling, retrieval-augmented generation (RAG), orchestration, memory/context management, and human-in-the-loop workflows.
• Manage dependencies between AI capabilities and traditional application components such as frontend, backend services, APIs, identity, databases, and enterprise integrations.
• Help teams distinguish between AI experimentation, production engineering, and product commitments, creating appropriate delivery mechanisms for each.
• Coordinate evaluation and readiness criteria for AI capabilities, including quality, accuracy, latency, reliability, safety, and cost.
• Facilitate resolution of issues involving model dependencies, prompts, agent behavior, data availability, integrations, and platform constraints.

Release & Production Readiness

• Coordinate end-to-end release planning across development, testing, security, infrastructure, and operations.
• Establish clear release readiness criteria and ensure teams address critical dependencies before production deployment.
• Partner with DevOps/SRE teams to strengthen CI/CD, automated testing, observability, rollback strategies, feature flags, and production monitoring.
• Ensure releases account for AI-specific operational considerations such as model availability, token consumption, latency, hallucination risk, agent failures, and third-party AI service dependencies.
• Facilitate post-release reviews and ensure production learnings are incorporated into subsequent planning.

Metrics & Continuous Improvement

Develop and maintain ART-level metrics covering

• PI objective achievement
• Predictability and delivery confidence
• Feature/epic flow
• Cycle and lead time
• Dependency aging
• Defects and production incidents
• Release frequency
• Deployment success
• AI quality/evaluation results
• Reliability and latency
• AI/model usage and cost

Use metrics to identify systemic bottlenecks and facilitate measurable improvements rather than using metrics solely for status reporting.

Required Qualifications

• 10+ years of experience in Agile delivery, program management, technical program management, or engineering delivery leadership.
• 5+ years of experience functioning as an RTE, Senior Scrum Master, Agile Program Lead, or equivalent cross-team delivery leader.
• Demonstrated experience coordinating multiple engineering teams delivering complex enterprise applications.
• Strong knowledge of SAFe, Scrum, Kanban, Agile planning, dependency management, and release management.
• Experience working with modern web/application architectures, APIs, cloud platforms, CI/CD, and DevOps practices.
• Working knowledge of Generative AI and LLM-based application architectures.
• Ability to facilitate technical conversations among AI engineers, software engineers, architects, product managers, security teams, and business stakeholders.
• Strong executive communication, facilitation, conflict resolution, and stakeholder-management skills.
• Proven ability to identify systemic impediments and drive resolution across organizational boundaries.

Preferred Qualifications

• SAFe Release Train Engineer (RTE), SAFe Practice Consultant (SPC), or equivalent certification.
• Experience delivering Generative AI or Agentic AI applications.
• Familiarity with concepts such as:

o LLMs and foundation models

o AI agents and multi-agent architectures

o Prompt engineering and prompt management

o Tool/function calling

o RAG and vector search

o Agent orchestration

o AI evaluation frameworks

o Guardrails and Responsible AI

o AI observability

o Model/token cost management

• Experience with public cloud and AI platforms such as Azure, AWS, or Google Cloud.
• Experience delivering applications in a regulated enterprise environment.
• Familiarity with modern web architectures, microservices, event-driven systems, API ecosystems, and enterprise identity/security.

Key Competencies

Execution Leadership: Creates clarity across complex, interdependent teams and drives commitments through completion.

Technical Fluency: Understands enough of the AI and application architecture to identify dependencies, risks, and sequencing challenges without attempting to replace engineerin