Senior Engineering Program Manager - Genai

Adobe Adobe · Enterprise · San Jose, CA

Senior Program Manager for GenAI features at Adobe, focusing on end-to-end delivery from concept to launch and scale. The role involves owning the feature roadmap, architecting and shipping agentic/RAG systems, driving adoption, managing governance and trade-offs, partnering deeply on technical execution (model selection, evaluation, MLOps), communicating progress and risk, codifying reusable patterns, and defining/monitoring outcome metrics. Requires 6+ years of TPM experience shipping AI/ML features, fluency in agentic architectures, RAG, prompt/eval frameworks, and MLOps, with a track record of zero-to-one feature ownership and strong executive communication.

What you'd actually do

  1. Define and lead the roadmap for GenAI-powered features from concept to launch, aligning scope and sequencing with business priorities.
  2. Lead and facilitate the design and delivery of the AI agents, multi-agent orchestration, and RAG pipelines underlying the feature, from prototype through production-grade deployment.
  3. Own the process for go-to-market and adoption plan; run pilots, gather usage signals, iterate on feedback, and build the mechanisms that move the feature from experimental to default usage.
  4. Set facilitation for prioritization and resourcing calls across workstreams (model work, UX, infra, QA).
  5. Work shoulder-to-shoulder with engineers on model selection, compose and evaluation systems, MLOps practices, and orchestration develop.

Skills

Required

  • 6+ years in technical program management
  • direct experience shipping AI/ML or GenAI-powered features in production
  • Working fluency in agentic architectures, RAG pipelines, prompt/eval frameworks, and MLOps
  • Track record of owning a feature from zero-to-one through scale, including adoption strategy and outcome measurement
  • Strong executive communication skills
  • Bias toward direct, risk-calibrated judgment

Nice to have

  • experience with model selection
  • experience with compose and evaluation systems
  • experience with MLOps practices
  • experience with orchestration develop

What the JD emphasized

  • Own end-to-end delivery of GenAI-powered features
  • technically skilled PGM role
  • lead the roadmap
  • develop system solutions
  • accountable for adoption and results
  • intersection of product strategy, applied AI architecture, and cross-functional execution
  • Own the Feature Roadmap End-to-End
  • Make the call on model bets and platform direction
  • Architect and Ship Agentic/RAG Systems
  • Partner directly with engineering on system architecture, not just program tracking
  • Drive Adoption from Beta to Default
  • Run Governance and Trade-offs Within the Feature Team
  • Partner Deeply on Technical Execution
  • Provide credible, hands-on technical review and pushback
  • this isn't a coordination-only role
  • Communicate Progress and Risk Upward
  • Codify Reusable Patterns
  • Own Outcome Metrics
  • direct experience shipping AI/ML or GenAI-powered features in production
  • Working fluency in agentic architectures, RAG pipelines, prompt/eval frameworks, and MLOps
  • able to engage credibly with engineers on design trade-offs, not just track them
  • Track record of owning a feature from zero-to-one through scale
  • Bias toward direct, risk-calibrated judgment over neutral status reporting

Other signals

  • GenAI-powered features
  • AI agents
  • RAG pipelines
  • multi-agent orchestration
  • production-grade deployment
  • model selection
  • compose and evaluation systems
  • MLOps practices
  • orchestration develop