Optum 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 advantages 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.

We're looking for a highly skilled Lead Generative AI & Agentic AI Architect to drive the design, development, and enterprise adoption of Large Language Model (LLM), Generative AI, and Agentic AI solutions. This role is responsible for defining enterprise AI architecture, establishing AI platform capabilities, developing domain-specific AI systems, and operationalizing AI solutions that deliver measurable business value at scale. - Primary Responsibilities :

- Enterprise AI Architecture & Strategy

- Lead the architecture, design, and implementation of enterprise-scale Generative AI and Agentic AI solutions aligned with business objectives

- Define enterprise AI architecture standards, reference architectures, governance models, and platform capabilities supporting scalable AI adoption

- Evaluate, benchmark, select, and operationalize proprietary and open-source foundation models based on reasoning capability, response quality, latency, scalability, security, and cost considerations

- Design multi-model AI architectures and intelligent routing strategies that dynamically select optimal models based on workload requirements, performance characteristics, and operational efficiency

- Establish reusable AI frameworks, accelerators,



and architecture patterns that enable rapid enterprise adoption of Generative AI capabilities

- Foundation Models & Model Engineering

- Design, develop, fine-tune, and operationalize foundation models, custom language models, and domain-specific AI solutions

- Supervised Fine-Tuning (SFT)

- LoRA

- QLoRA

- PEFT

- Instruction Tuning

- Domain Adaptation

- Optimize model performance through inference tuning, quantization strategies, context management, and workload optimization

- Manage model lifecycle processes including:

- Model versioning

- Validation and testing

- Release management

- Production readiness reviews

- Governance and compliance controls

- Generative AI & Retrieval Architecture

- Design end-to-end retrieval architectures including:

- Document ingestion

- Content processing and chunking

- Embedding generation

- Vector indexing

- Semantic retrieval

- Grounding strategies

- Retrieval optimization

- Build AI-ready knowledge platforms that enable accurate, context-aware, and explainable responses

- Design semantic search, hybrid search, reranking, and vector retrieval frameworks to maximize retrieval quality and answer relevance

- Establish knowledge retrieval architectures that support enterprise search, copilots, intelligent assistants, and decision-support systems

- Agentic AI & Intelligent Automation

- Design and develop Agentic AI systems capable of:

- Autonomous reasoning

- Planning and decision-making

- Task execution

- Workflow orchestration





- Tool utilization

- Build and operationalize single-agent and multi-agent architectures for enterprise use cases

- Integrate AI agents with:

- APIs

- Databases

- Knowledge repositories

- Business workflows

- External services

- Design context engineering strategies including:

- Agent memory management

- Session persistence

- Context orchestration

- Retrieval coordination

- Long-running conversation management

- AI Platforms & Enterprise Integration

- Build enterprise AI platforms that provide centralized access, orchestration, governance, and management across multiple AI model providers

- Design AI gateway capabilities supporting:

- Model routing

- Provider abstraction

- Policy enforcement

- Access management

- Usage governance

- Cost controls

- Leverage cloud-based AI platforms including:

- Azure OpenAI

- Azure AI Foundry

- AWS Bedrock

- Google Vertex AI

- Comparable enterprise AI ecosystems

- AI Quality, Evaluation & Observability

- Implement end-to-end AI observability across agentic systems, retrieval frameworks, AI workflows, and foundation model deployments

- Develop capabilities including:

- Prompt tracing

- Agent tracing

- Workflow tracing

- Retrieval tracing

- Inference monitoring

- Operational telemetry

- Define and continuously improve AI quality metrics including:

- Response accuracy

- Groundedness

- Hallucination rates

- Latency

- Throughput

- Token consumption

- Task completion rates

- User satisfaction

- Design automated evaluation frameworks leveraging:

- Benchmark datasets

- Human feedback

- Synthetic evaluations

- Regression testing

- Production telemetry

- Responsible AI, Governance & Cost Optimization

- Establish Respo

📌 Senior Ai/ml Engineer (Gen Ai Specialist) (Bengaluru)
🏢 UnitedHealth Group
📍 Bengaluru