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

New York Life · New York, NY · 3 days ago
Engineering$148k/yrFull-time

About the role

The Release Train Engineer (RTE) leads delivery of a next-generation Agentic AI web application. This role sits at the intersection of product, engineering, AI/ML, architecture, security, and operations.

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.

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: LLMs and foundation models, AI agents and multi-agent architectures, prompt engineering and prompt management, tool/function calling, RAG and vector search, agent orchestration, AI evaluation frameworks, guardrails and Responsible AI, AI observability, 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.

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