Senior AI or ML Engineer - Conversational AI, Bot Development

Requisition Number: 2396028

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 wor