Hyderabad Telangana Hospital patient relation Jobs – 109 Open Jobs Today

Director - AI Engineering
Providence Global Center —Hyderabad, Telangana
- Part-time
- System design
- Research
- Master's degree
- Health insurance
Lead HCM Developer
Providence Global Center —Hyderabad, Telangana
- Part-time
- Oracle
- SQL
- Human resources
- Health insurance
Sr. ERP Developer
Providence Global Center —Hyderabad, Telangana
- Part-time
- Oracle
- ERP systems
- SQL
- Health insurance
Lead Data Engineer
Providence Global Center —Hyderabad, Telangana
- Part-time
- Azure
- Computer Science
- SQL
- Health insurance
Principal Software Engineer
Providence Global Center —Hyderabad, Telangana
- Part-time
- Azure
- Computer Science
- SQL
- Health insurance
Principal Cybersecurity Architect
Providence Global Center —Hyderabad, Telangana
- Part-time
- Analysis skills
- Communication skills
- Health insurance
Senior ERP Developer
Providence Global Center —Hyderabad, Telangana
- Part-time
- Oracle
- ERP systems
- SQL
- Health insurance

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Director - AI Engineering

Providence Global Center
Hyderabad, Telangana

Apply Now

Job details

Part-time | Full-time

Benefits

Health insurance

Qualifications

Law
MCP
System design
Research
Enterprise architecture
Master's degree
Bachelor's degree
Distributed systems
Scalability
AI
Leadership
SDLC

Full job description

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

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:

Distributed Systems & AI Architecture Mastery
Deep expertise in distributed system design, architecture patterns, reusable AI frameworks, and resilience strategies for large‑scale, production AI systems.
Multi‑Model & Multi‑Agent Orchestration
Ability to design and oversee complex agentic systems—including reasoning orchestration, coordination patterns, advanced agent architectures, and bounded autonomy.
Context, Memory & Reasoning Engineering
Mastery of context orchestration, memory management, multi‑source context fusion, and reusable “skills.md / workbooks” that standardize how intelligence is grounded and reused.
Model Strategy & Selection Frameworks
Expertise in enterprise‑grade model selection—balancing accuracy, explainability, latency, cost, data sensitivity, and governance requirements by use case.
AI Quality, Benchmarking & Observability
Define AI quality frameworks, benchmark systems, evaluation pipelines, and observability practices covering accuracy, drift, reasoning quality, cost efficiency, and reliability.
Cost, Latency & Operational Optimization
Deep understanding of cost and latency trade‑offs across models, agents, orchestration layers, and infrastructure—ensuring AI systems are economically viable at scale

Professional Experience/Qualifications

Bachelors/ Masters in STEM. Healthcare areas of specialization with ongoing engagement in emerging AI technologies, agentic systems, and applied research is preferred
15+ years of engineering experience, with 8–10+ years leading large‑scale platform or product engineering teams, including senior architects and domain experts delivering production‑grade systems.
Proven track record building and scaling AI‑powered platforms or products in complex, distributed environments—moving solutions from experimentation to enterprise adoption, reuse, and sustained value.
Deep experience designing and governing advanced AI systems, including multi‑model, multi‑agent architectures, orchestration frameworks, and reasoning systems, operating under clear performance, cost, and reliability constraints.
Demonstrated leadership in AI governance and responsible AI, including defining frameworks for model lifecycle management, quality benchmarking, compliance, risk controls, auditability, and ethical AI practices, ideally in regulated or high‑trust environments.
Strong background in enterprise architecture and distributed systems, with the ability to oversee decisions on scalability, latency, resilience, cost optimization, and technical debt across platforms and products.
Experience driving standardized AI SDLC (AI‑DLC) practices—creating playbooks, runbooks, operating procedures, and architectural decision records that enable consistency, speed, and safety across teams.

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.

Apply Now

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hospital patient relation jobs in hyderabad telangana

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