Optum
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Chennai · On-site · Oct 14
Healthcare Services & Hospitals · 10000+ Employees · Eden Prairie, US
Optum, part of the UnitedHealth Group family of businesses, is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.
Hiring: Engineering
What employees say
+ Job assurance is stable even when no projoect is there
− salary hike could be better for experienced candidates and promotion is impossible
More reviews on the company profile.
Interview experience · TDP Intern
They asked for introduction, resume absed questions. Discussion about projects. One DSA question was of adding 2 number without '+' operator, other was recursive factorial calculation. Asked SQL vs NOSQL choice.
Easy difficulty · India · 738 reports
More interview insightsJob description
Overview
Primary Responsibilities
Responsibilities
- Define and lead the enterprise Data AI Platform Strategy, ensuring scalable, secure, resilient, and cost-efficient platforms for Analytics, ML, GenAI, and Agentic AI
- Build AI-ready data foundations using semantic layers, metadata management, data lineage, knowledge graphs, and governance frameworks
- Lead data engineering teams responsible for ingestion, transformation, storage, pipelines, APIs, data products, and real-time data solutions
- Establish engineering standards, reusable frameworks, and drive modernization of legacy systems into cloud-native architectures
- Partner with Data Science and AI teams to operationalize ML, GenAI, and Agentic AI solutions
- Enable capabilities such as feature stores, vector databases, embeddings, RAG, model deployment, monitoring, observability, explainability, and Responsible AI
- Drive enterprise-wide data governance, including data quality, stewardship, cataloging, lineage, master data management, privacy, and compliance
- Govern both AI training datasets and AI-generated outputs
- Promote a Data-as-a-Product operating model with defined ownership, SLAs, and quality standards
- Prioritize platform and data initiatives based on business value, AI readiness, and measurable outcomes
- Evaluate and implement emerging technologies including GenAI, Agentic AI, Data Fabric, Semantic Layers, Knowledge Graphs, and Intelligent Automation
- Lead proofs of concept and scale successful innovations across the enterprise
- Partner with business, product, analytics, and technology leaders to align platform investments with strategic objectives
- Present technology strategy and roadmap recommendations to executive leadership
- Manage budgets, vendors, cloud spend, operational performance, and platform reliability
- Establish KPIs for performance, availability, productivity, automation, and cost optimization
- Build, mentor, and develop high-performing Data AI engineering teams
- Foster innovation, accountability, continuous learning, talent development, and career growth
- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements
Qualifications
- Extensive leadership experience in Data Engineering, Data Platforms, AI/ML Platforms, or Enterprise Data Architecture
- Experience implementing Data-as-a-Product frameworks and enterprise data strategies
- Experience managing large-scale engineering organizations, budgets, vendors, and cloud cost optimization initiatives
- Solid expertise in cloud-based data ecosystems and modern data platform architectures
- Deep knowledge of data engineering concepts including data pipelines, APIs, data products, streaming, and real-time processing
- Hands-on understanding of AI/ML operationalization, including:
- MLOps
- GenAI
- Agentic AI
- Vector Databases
- RAG (Retrieval-Augmented Generation)
- Embeddings
- Model Deployment Monitoring
- Responsible AI
- Solid understanding of enterprise data governance, data quality, lineage, metadata management, cataloging, MDM, privacy, and regulatory compliance
- Knowledge of emerging technologies such as:
- GenAI
- Agentic AI
- Data Fabric
- Knowledge Graphs
- Semantic Layers
- Intelligent Automation
- Solid stakeholder management and executive communication skills
- Proven ability to build and lead high-performing teams across data engineering, analytics, governance, and AI domains
- Demonstrated success in driving platform modernization, digital transformation, and enterprise-scale technology adoption
- Data quality and reliability
- AI adoption and business impact
- Platform availability and performance
- Data product adoption
- Engineering productivity and automation
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Job application FAQ
Last updated 21 October 2026
- How do I apply for Director AI/ML Engineering at Optum?
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- Is Director AI/ML Engineering remote or on-site in Chennai, Tamil Nadu?
- This listing is marked on_site with location Chennai, Tamil Nadu. Confirm details on the job description before applying.
- What skills matter for this Director AI/ML Engineering role at Optum?
- Key skills for this role include skills listed in the job description. Upload a resume to see which requirements you already meet and which are gaps.