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 Perks
- Inclusive Leadership
- Reimagining Healthcare
- Competitive Pay
- Supportive Reporting Relation

The Opportunity

- The Director - AI Engineering (Products & Governance) will play a pivotal role in engineering scalable, production grade AI products while embedding governance, risk, and responsible‑AI controls directly into the AI development lifecycle. This role is accountable for translating organizational, regulatory, and ethical AI policies into practical engineering standards, reference architectures, and automated guardrails across model development, deployment, and operations.
- The role partners closely with business stakeholders, product leaders, department leaders, legal, risk, and compliance teams to enable rapid AI innovation without compromising trust, safety, or regulatory obligations.



The Director is accountable for strengthening regional AI engineering and governance capabilities in service of Providence and other partnering health systems ensuring AI products are robust, auditable, explainable, and compliant by design .

Key Responsibilites

Strategic :

- AI Platform & Ecosystem Strategy
- Define the enterprise strategy for AI platforms, agentic systems, and reusable frameworks—balancing scalability, interoperability, cost, and long‑term flexibility across products and domains.
- Product‑Driven AI Governance Strategy
- Shape AI governance as an enabler of product velocity—embedding compliance, risk management, and ethical controls directly into architectures, SDLC, and operating models rather than as after‑the‑fact checks.
- Enterprise Model & Tooling Strategy (Build vs. Buy)
- Lead strategic evaluation of foundation models, orchestration frameworks, MCP ecosystems, and tools—making informed build‑vs‑buy decisions aligned to cost, latency, risk, vendor lock‑in, and regulatory exposure.
- AI Investment & Value Realization Frameworks
- Define and track AI‑for‑Engineering KPIs (cost, latency, throughput, reuse, quality, adoption, reliability) that connect technical choices to measurable business and product outcomes.
- Future‑Ready AI Architecture Vision
- Anticipate advances in multi‑modal AI, agentic reasoning, and distributed systems, translating emerging trends into a pragmatic enterprise roadmap rather than experimental sprawl.




- Information Architecture & Data Readiness Strategy
- Establish the strategy for AI‑ready information architectures and multi‑modal data ecosystems that support reasoning, grounding, memory, and context fusion at scale.
- AI Ops Strategy
- Responsible for establishing an AI Ops strategy across LLM and Agent Ops, ensuring continuous observability, evaluation, and feedback loops.

Leadership :

- Technical Leadership of Senior Experts
- Lead, mentor, and challenge highly experienced AI and systems engineers—shifting focus from individual implementation to architectural judgment, quality, and scale.
- Architecture Governance & Decision Stewardship
- Chair design reviews, own architectural decision records (ADRs), and resolve complex trade‑offs across performance, safety, cost, and maintainability at an enterprise level.
- Operating Model & AI‑DLC Ownership
- Establish and evolve the AI SDLC (AI‑DLC), ensuring consistent patterns for development, evaluation, deployment, monitoring, and iteration across all AI initiatives.
- Cross‑Functional Executive Partnership
- Partner with product, security, legal, compliance, and clinical/business leaders to align technical direction with enterprise priorities and risk posture.
- Standardization without Innovation Friction
- Drive adoption of playbooks, runbooks, SOPs, and reusable patterns while preserving room for innovation and domain‑specific differentiation.
- Culture of Engineering Excellence & Accountability
- Build a culture that values clarity, documentation, benchmarking, operational rigor, and learning—where engineers are accountable for production impact, not just clever designs.

Technical :

- **Distribute

📌 Director - Ai Engineering (Hyderabad)
🏢 PROVIDENCE GLOBAL CENTER
📍 Hyderabad