Principal Product Manager, AI Sdlc

SoFi SoFi · Fintech · San Francisco, CA · Engineering

Principal Product Manager to define and scale SoFi's AI-powered SDLC platform, integrating AI into the product development process from discovery to continuous improvement. This role focuses on platform leadership at the intersection of AI, developer experience, CI/CD, testing, observability, and governance, defining how AI agents generate code, tests, and documentation, and integrating them into development workflows. Requires strong technical fluency, enterprise influence, and experience shipping LLM-powered or agent-driven products.

What you'd actually do

  1. Own the multi-year product strategy for AI across the Product and Software Development Lifecycle.
  2. Define standards for “Spec-to-Code-to-Deploy” workflows, where structured specifications can trigger AI agents to generate production-ready code, tests, and documentation.
  3. Define how AI agents integrate into specs, repositories, CI/CD pipelines, testing frameworks, and operational systems and the technologies required to enable it.
  4. Run fast build-measure-learn loops with internal developer users.
  5. Establish measurable evaluation frameworks to ensure AI-driven workflows are reliable, safe, and continuously improving.

Skills

Required

  • 10+ years of Product Management experience
  • significant experience building developer platforms, CI/CD systems, testing/quality tooling, or internal engineering products
  • Demonstrated success shipping LLM-powered or agent-driven products into production
  • Deep familiarity with agentic patterns (tool use, planning/execution loops, structured prompting, evaluation strategies)
  • Experience designing platform-scale products with APIs, extensibility, governance, and enterprise adoption in mind
  • Strong architectural intuition and the ability to read and reason about code
  • Comfort collaborating directly with senior engineers on implementation trade-offs
  • Experience defining telemetry requirements and AI evaluation metrics
  • Exceptional discovery skills: problem framing, hypothesis formation, prioritization, ROI analysis
  • Experience defining measurable success criteria and evaluation frameworks for AI systems
  • Ability to balance long-term platform investments with near-term demonstrable wins
  • Proven track record driving cross-team initiatives involving engineering, data science, infrastructure, security, and compliance
  • Ability to align diverse stakeholders around a bold but grounded vision
  • Strong storytelling and executive communication skills

What the JD emphasized

  • AI-powered SDLC platform
  • integrate AI into every facet of our product development process
  • AI as the engine of development velocity
  • AI agents to generate production-ready code, tests, and documentation
  • AI agents integrate into specs, repositories, CI/CD pipelines, testing frameworks, and operational systems
  • shipping LLM-powered or agent-driven products into production
  • agentic patterns (tool use, planning/execution loops, structured prompting, evaluation strategies)
  • platform leadership role
  • multi-year product strategy
  • production-ready code
  • internal developer users
  • measurable evaluation frameworks
  • AI autonomy
  • AI-enabled development standards
  • senior leadership
  • startup founder inside the company
  • scalable platform capabilities
  • principal engineers
  • customers
  • strong technical fluency
  • enterprise influence
  • demonstrated experience working with AI in an engineering or product management role
  • significant experience building developer platforms, CI/CD systems, testing/quality tooling, or internal engineering products
  • Deep familiarity with agentic patterns
  • platform-scale products
  • governance
  • enterprise adoption
  • senior engineers
  • telemetry requirements
  • AI evaluation metrics
  • Exceptional discovery skills
  • measurable success criteria
  • evaluation frameworks for AI systems
  • long-term platform investments
  • near-term demonstrable wins
  • cross-team initiatives
  • engineering, data science, infrastructure, security, and compliance
  • align diverse stakeholders
  • bold but grounded vision
  • executive communication skills

Other signals

  • AI-powered SDLC platform
  • integrate AI into every facet of our product development process
  • AI as the engine of development velocity
  • AI agents to generate production-ready code, tests, and documentation
  • AI agents integrate into specs, repositories, CI/CD pipelines, testing frameworks, and operational systems
  • shipping LLM-powered or agent-driven products into production
  • agentic patterns (tool use, planning/execution loops, structured prompting, evaluation strategies)