Senior AI or ML Engineer - Conversational AI, Bot Development
Optum (UnitedHealth Group) · Healthcare & Pharma
- Noida, Uttar Pradesh, India
- On-site
- Posted today
- Data & AI
About the job
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 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.
Primary Responsibilities:
Conversational AI and Bot Development - Design, develop, test, deploy, and continuously improve enterprise-grade chatbots, voice bots, virtual assistants, and copilots
Build multi-turn conversational experiences incorporating intent recognition, entity extraction, dialogue and session management, context retention, disambiguation, personalisation, and task completion
Develop conversational journeys across chat, voice, web, mobile, contact-centre, and enterprise collaboration channels
Implement handling for interruptions, corrections, ambiguous requests, incomplete information, fallbacks, escalation, and human-agent hand-off
Integrate bots with enterprise APIs, knowledge repositories, workflow platforms, identity services, contact-centre solutions, and backend applications
Apply conversation-design principles to deliver natural, accessible, consistent, and task-oriented user experiences
Agentic AI Solution Design and Implementation - Design and build agentic bots capable of reasoning, planning, function calling, tool usage, memory management, knowledge retrieval, API interaction, and multi-step workflow execution
Develop single-agent and multi-agent solutions using frameworks such as Google ADK, LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or similar technologies
Implement orchestration patterns including supervisor, router, planner-executor, specialist-agent, sequential, parallel, and human-in-the-loop workflows
Define agent instructions, tools, state, memory, permissions, and operational boundaries to support predictable and secure behaviour
Implement approval checkpoints, restricted tool access, retry and timeout policies, action validation, auditability, and safe termination
Build graceful fallback and escalation mechanisms when an agent lacks sufficient information, confidence, permissions, or capability
Google Conversational AI and Agent Ecosystem - Design and optimise conversational experiences using Google GECX, including flows, intents, entities, routes, fulfilment, parameters, events, integrations, and environment configuration
Develop and orchestrate AI agents using Google ADK, including agent definitions, tools, sessions, state, memory, workflow coordination, and evaluation
Integrate Google conversational AI solutions with Gemini models, enterprise knowledge sources, APIs, webhook services, and backend applications
Develop reusable bot components, agent templates, tools, connectors, conversation patterns, prompts, and evaluation assets
Troubleshoot issues across conversation flows, agent orchestration, fulfilment services, session state, authentication, APIs, channels, and production telemetry
Hands-On Engineering and Cloud Development - Contribute directly to bot configuration, software development, prompt engineering, agent orchestration, integration, testing, debugging, and production delivery
Build fulfilment services, APIs, microservices, reusable libraries, and connectors using Python, Java, Spring Boot, or comparable technologies
Integrate bots and agents with REST APIs, databases, event streams, workflow engines, identity providers, CRM platforms, claims systems, and knowledge repositories
Build secure, scalable, cloud-native AI solutions, preferably using Google Cloud, while supporting Azure-based environments where required
Apply modular design, source control, automated testing, code reviews, observability, documentation, and secure development practices
Ensure solutions meet enterprise requirements for reliability, privacy, security, scalability, resiliency, and operational readiness
DevOps, Governance and Operational Readiness - Build CI/CD pipelines for bot configurations, prompts, agent definitions, orchestration code, fulfilment services, infrastructure, and evaluation assets
Support containerised deployments using Docker, Kubernetes, Google Kubernetes Engine, Azure Kubernetes Service, or comparable platforms
Implement quality gates, security scanning, configuration validation, environment promotion, monitoring, rollback, and release governance
Establish logging, distributed tracing, dashboards, alerting, operational runbooks, incident triage, and recovery procedures
Apply DevOps, MLOps, and LLMOps practices to support controlled and continuous improvement
Implement authentication, authorisation, least-privilege access, secrets management, data protection, safe tool execution, and auditability
Ensure alignment with enterprise security, privacy, compliance, and Responsible AI requirements
Technical Leadership - Lead and mentor engineers delivering conversational AI, GenAI, and agentic bot solutions while remaining actively hands-on
Provide technical direction, conduct code and design reviews, and guide architecture, platform, and implementation decisions
Establish reusable standards, reference architectures, development guidelines, review checklists, and adoption playbooks
Build team capability in Google GECX, Google ADK, conversation design, agent orchestration, RAG, testing, LLMOps, cloud development, and Responsible AI
Communicate technical options, risks, dependencies, and trade-offs clearly to business and technology stakeholders
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
Required Qualifications:
Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical field; equivalent practical experience will also be considered
8+ years of experience in software engineering, conversational AI, AI/ML engineering, platform engineering, or distributed systems
Hands-on experience building AI agents using reasoning, planning, function calling, tools, memory, APIs, and multi-step workflows
Demonstrable hands-on experience developing production-grade chatbots, voice bots, virtual assistants, copilots, or conversational AI applications
Experience with at least one agent framework such as Google ADK, LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or equivalent
Experience integrating bots or agents with enterprise APIs, backend applications, databases, authentication services, workflow engines, and knowledge sources
Experience implementing RAG pipelines, including ingestion, chunking, embeddings, vector search, semantic retrieval, reranking, grounding, and response generation
Experience developing backend fulfilment or integration services; Java or Spring Boot experience is beneficial
Experience with cloud-native development on Google Cloud, Azure, or another major cloud platform
Experience with Docker, Kubernetes, CI/CD pipelines, logging, monitoring, distributed tracing, and production troubleshooting
Experience testing conversational and agentic applications across unit, integration, regression, end-to-end, prompt, retrieval, tool, and workflow scenarios
Solid experience with multi-turn conversations, intents, entities, dialogue flows, context management, session state, fulfilment, fallbacks, and escalation
Solid understanding of prompt engineering, agent instructions, tool definition, context management, model evaluation, guardrails, and Responsible AI controls
Proficiency in Python and solid knowledge of APIs, microservices, asynchronous processing, automated testing, observability, and scalable system design
Proven ability to optimise AI solutions for task completion, conversation quality, latency, retrieval effectiveness, cost, reliability, scalability, and user experience
Proven ability to lead technical delivery, mentor engineers, review code, guide architectural decisions, and communicate effectively with stakeholders
Willingness to remain hands-on in bot development, coding, integration, testing, debugging, and production support
Preferred Qualifications:
Hands-on experience with Google GECX, including flows, intents, entities, routes, fulfilment, parameters, event handlers, environments, testing, and production deployment
Hands-on experience with Google Agent Development Kit (ADK) for developing, orchestrating, evaluating, or deploying AI agents
Experience integrating GECX or ADK solutions with Gemini models, enterprise APIs, webhook services, knowledge sources, and downstream systems
Experience implementing single-agent, multi-agent, supervisor, router, planner-executor, specialist-agent, or agent-to-agent patterns
Experience building enterprise voice bots or contact-centre solutions involving speech recognition, text-to-speech, interruption handling, escalation, and call transfer
Experience with Google Cloud services used to host, secure, integrate, monitor, and operate conversational AI workloads
Experience with Azure OpenAI, Azure AI Search, OpenAI APIs, Anthropic Claude, Gemini, open-source LLMs, or model-hosting platforms
Experience with vector search technologies such as Vertex AI Vector Search, Azure AI Search, Pinecone, Weaviate, FAISS, Milvus, Chroma, or Elasticsearch
Experience with LLM evaluation and monitoring tools such as LangSmith, PromptFlow, Ragas, DeepEval, TruLens, Arize Phoenix, or similar platforms
Experience creating golden conversation datasets, automated evaluation suites, red-team scenarios, and conversational analytics dashboards
Experience designing reusable bot frameworks, agent platforms, SDKs, tools, connectors, accelerators, or reference architectures
Experience integrating conversational agents with CRM, claims, contact-centre, document-management, knowledge-management, or workflow platforms
Experience with NLU, NLP, speech, multimodal AI, conversation analytics, security, privacy, and Responsible AI
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.