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Principal Product Manager

About Providence

Providence, one of the US’s largest not-for-profit healthcare systems, is committed to high quality, compassionate healthcare for all. Driven by the belief that health is a human right and the vision, ‘Health for a better world’, Providence and its 121,000 caregivers strive to provide everyone access to affordable quality care and services.

Providence has a network of 51 hospitals, 1,000+ care clinics, senior services, supportive housing, and other health and educational services in the US.

Providence India is bringing to fruition the transformational shift of the healthcare ecosystem to Health 2.0. The India center will have focused efforts around healthcare technology and innovation, and play a vital role in driving digital transformation of health systems for improved patient outcomes and experiences, caregiver efficiency, and running the business of Providence at scale.

Why Us?

Best In-class Benefits
Inclusive Leadership
Reimagining Healthcare
Competitive Pay
Supportive Reporting Relation

About Us

We are a technology-driven organization building enterprise-scale platforms that power modern Software Engineering and AI Engineering. Our mission is to accelerate innovation by embedding Artificial Intelligence directly into software engineering workflows, developer platforms, and business operations.

We believe AI should not exist as separate experiments or disconnected tools. Instead, AI must be integrated into the core engineering ecosystem with the same standards of reliability, scalability, governance, observability, and operational excellence expected from any production platform.

Our platform strategy spans both:

Software Development Lifecycle (SDLC)
AI Development Lifecycle (AIDLC)

We are investing heavily in AI-powered engineering platforms, developer productivity, automation, agentic workflows, reusable platform services, and enterprise AI governance.

Role Overview

We are looking for an experienced Product Manager to lead the strategy, vision, and execution of next-generation Engineering and AI Platforms.

This role sits at the intersection of:

Platform Engineering
Software Engineering
Cloud Engineering
AI Engineering
Developer Experience
Enterprise Architecture
Production Reliability

You will own products and platforms that enable engineers, architects, data scientists, AI engineers, and business teams to build, deploy, operate, and scale software and AI systems efficiently and securely.

You will help shape the future state where Software Development Lifecycle (SDLC) and AI Development Lifecycle (AIDLC) converge into a unified engineering ecosystem.

Key Responsibilities

Product Strategy & Vision

Define and drive platform strategy for enterprise engineering ecosystems.
Develop and execute multi-year product roadmaps across Software Engineering and AI Engineering platforms.
Identify opportunities to leverage AI to improve developer productivity, engineering efficiency, platform operations, and business outcomes.
Build compelling product visions aligned with enterprise technology strategy.

Software Engineering Platforms

Own and evolve platforms including:

Internal Developer Platforms (IDP)
API Management Platforms
Microservices Ecosystems
CI/CD Platforms
DevOps Toolchains
Developer Experience Platforms
Platform Observability Solutions
Engineering Productivity Platforms

Drive:

Developer self-service capabilities
Platform standardization
Engineering automation
Accelerated software delivery
Operational excellence

AI Engineering Platforms

Lead product strategy and execution for:

Enterprise LLM Platforms
AIDLC Platforms
Agentic AI Platforms
AI Evaluation Frameworks
Prompt Engineering Platforms
RAG (Retrieval-Augmented Generation) Ecosystems
Multi-Agent Systems
Model Observability Platforms
AI Governance Services

Drive adoption of reusable AI capabilities and platform services across the organization.

SDLC + AIDLC Convergence

Establish a unified engineering operating model by integrating AI directly into software engineering workflows.

Examples include:

AI-driven requirements generation
Architecture assistants
Automated code generation
AI-assisted testing
Security automation
Release intelligence
Operational copilots
AI-driven incident management

Champion the integration of AI into:

Development workflows
Platform engineering
DevSecOps
Cloud operations
Software quality processes

Productization of Platform Capabilities

Lead the development of reusable platform assets including:

APIs
SDKs
Frameworks
Shared libraries
Automation services
AI agents
Platform accelerators

Focus on:

Reusability
Consistency
Governance
Scalability
Enterprise adoption

Platform Governance

Define and drive governance frameworks covering:

Software Systems

Security
Compliance
Availability
Reliability
Resiliency
Scalability

AI Systems

Responsible AI
Model governance
Prompt governance
Data privacy
Explainability
Risk management
Human oversight

Engineering & AI Metrics

Define measurable success outcomes and platform KPIs.

Software Engineering Metrics

Track and improve:

Deployment Frequency
Lead Time for Changes
Change Failure Rate
Mean Time To Recovery (MTTR)
Platform Adoption
Developer Productivity
Service Reliability

AI Engineering Metrics

Track and improve:

Accuracy
Response Quality
Hallucination Rate
Cost Per Request
Token Consumption
Retrieval Accuracy
Latency
Automation Coverage
AI Adoption
Agent Effectiveness

Use metrics to drive investment decisions and roadmap prioritization.

Cross-Functional Leadership

Partner closely with:

Engineering Leaders
AI/ML Engineers
Platform Architects
DevOps Teams
Security Teams
Data Teams
Product Leaders
Executive Leadership

Build alignment across business and technology stakeholders.

Production Excellence

Ensure production-ready platforms through strong operational practices.

Drive:

Reliability Engineering
Platform Observability
Capacity Planning
Cost Optimization
AI Monitoring
Incident Response
Operational Governance

What Your Day Could Look Like

You may be:

Working with Engineering Teams

Reviewing API designs
Evaluating platform architectures
Discussing microservice scalability
Prioritizing platform investments

Collaborating with AI Teams

Designing RAG architectures
Evaluating agent workflows
Reviewing model evaluation strategies
Defining AI governance requirements

Reviewing Production Telemetry

Software Systems:

Latency
Error rates
Throughput
Availability

AI Systems:

Hallucinations
Drift
Retrieval performance
Inference latency
Token consumption

Driving Strategic Decisions

Balancing:

Innovation vs Stability
Speed vs Governance
Build vs Buy
Cost vs Performance
Standardization vs Flexibility

Managing Platform Priorities

Making roadmap decisions across:

Engineering productivity
Platform modernization
AI adoption
Technical debt reduction
Reliability improvements

Required Qualifications

Experience

8+ years in Product Management, Platform Management, Engineering Leadership, or related areas.
Experience delivering enterprise-scale software products and platforms.
Proven track record building engineering platforms or developer-focused products.
Experience working with AI/ML-powered products and platforms.

Technical Knowledge

Strong understanding of:

Software Engineering

APIs
Microservices
Distributed Systems
Cloud Native Architectures
Platform Engineering
Site Reliability Engineering
DevOps Practices
CI/CD Pipelines

AI Engineering

Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Agentic AI Systems
Prompt Engineering
Model Evaluation
AI Governance
AI Observability
AIDLC Frameworks

Preferred Qualifications

Experience with:

Azure AI Services
OpenAI Ecosystems
Kubernetes
Service Mesh Architectures
Internal Developer Platforms
Multi-Agent Platforms
AI Governance Frameworks
Enterprise Architecture
Engineering Productivity Platforms

MBA or advanced technical degree preferred but not required.

Leadership Competencies

We are looking for someone who:

Thinks in platforms, not individual features
Drives data-informed decisions
Challenges assumptions
Balances innovation with operational excellence
Influences without direct authority
Communicates effectively with executives and engineers
Understands both customer outcomes and technical realities
Thrives in ambiguity and complexity

Providence’s vision to create ‘Health for a Better World’ aids us to provide a fair and equitable workplace for all in our employment, whether temporary, part-time or full time, and to promote individuality and diversity of thought and background, and acknowledge its role in the organization’s success. This makes us committed towards equal employment opportunities, regardless of race, religion or belief, color, ancestry, disability, marital status, gender, sexual orientation, age, nationality, ethnic origin, pregnancy, or related needs, mental or sensory disability, HIV Status, or any other category protected by applicable law. In furtherance to our mission in building a more inclusive and equitable environment, we shall, from time to time, undertake programs to assist, uplift and empower underrepresented groups including but not limited to Women, PWD (Persons with Disabilities), LGTBQ+ (Lesbian, Gay, Transgender, Bisexual or Queer), Veterans and others. We strive to address all forms of discrimination or harassment and provide a safe and confidential process to report any misconduct.

Contact our Integrity hotline also, read our Code of Conduct.

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