Bangalore, Karnataka, India
Actively hiring, first seen by us todayDesign, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI
Build and deploy production LLM agents that automate detection, triage, and remediation of platform and application issues
Implement agent orchestration, including tool/function calling, multi-step planning, multi-agent handoffs, memory, and state management
Primary Responsibilities: Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI Build and deploy production LLM agents that automate detection, triage, and remediation of platform and application issues
Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI Build and deploy production LLM agents that automate detection, triage, and remediation of platform and application issues Design and tune RAG pipelines over runbooks, incident history, logs, code, and internal documentation, including chunking strategy, embedding selection, vector store design, hybrid/semantic search, and reranking
Design and tune RAG pipelines over runbooks, incident history, logs, code, and internal documentation, including chunking strategy, embedding selection, vector store design, hybrid/semantic search, and reranking Implement agent orchestration, including tool/function calling, multi-step planning, multi-agent handoffs, memory, and state management Build supporting infrastructure and software layers for agents, including tool wrappers, guardrails, human-in-the-loop approval paths, and fallback behavior
Bachelor's degree or equivalent experience (e.g., 10+ years of software engineering or machine learning engineering experience in lieu of a degree)
10 + years of software engineering or machine learning engineering experience
10+ years of experience with proficiency in languages such as Java, C#, Python, or Go
6+ years of experience integrating third-party APIs and building backend services that run in production
6+ years of experience with cloud platforms (Azure, AWS, or GCP), containers, and CI/CD pipelines 2+ years of hands-on experience building with LLMs, including prompt engineering, tool/function calling, and agent or multi-step orchestration
2+ years of experience designing and shipping RAG systems in production, including embeddings, vector databases (e.g., Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation
Experience with model fine-tuning or parameter-efficient fine-tuning (PEFT) techniques
Experience integrating agents with enterprise observability and security platforms via APIs and MCP-style tool interfaces
Proven ability to work across multidisciplinary teams (e.g., SRE, InfoSec, platform engineering) and translate operational pain points into technical requirements
Required Qualifications: - Bachelor's degree or equivalent experience (e.g., 10+ years of software engineering or machine learning engineering experience in lieu of a degree) - 10 + years of software engineering or machine learning engineering experience
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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At UnitedHealth Group, jobs usually come down by about day 11.
From 4,397 similar postings that came down, and 803 of UnitedHealth Group’s. Coming down is not always a hire.
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- 10 + years of software engineering or machine learning engineering experience - 10+ years of experience with proficiency in languages such as Java, C#, Python, or Go - 6+ years of experience integrating third-party APIs and building backend services that run in production
- 2+ years of experience designing and shipping RAG systems in production, including embeddings, vector databases (e.g., Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation - 2+ years of experience with Python, including working knowledge of agent frameworks (e.g., LangGraph, LangChain, LlamaIndex, Semantic Kernel, or CrewAI) - 2+ years of experience building LLM evaluation and testing workflows rather than relying on manual spot checks
- 6+ years of experience integrating third-party APIs and building backend services that run in production - 6+ years of experience with cloud platforms (Azure, AWS, or GCP), containers, and CI/CD pipelines 2+ years of hands-on experience building with LLMs, including prompt engineering, tool/function calling, and agent or multi-step orchestration - 2+ years of experience designing and shipping RAG systems in production, including embeddings, vector databases (e.g., Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation
- 6+ years of experience with cloud platforms (Azure, AWS, or GCP), containers, and CI/CD pipelines 2+ years of hands-on experience building with LLMs, including prompt engineering, tool/function calling, and agent or multi-step orchestration - 2+ years of experience designing and shipping RAG systems in production, including embeddings, vector databases (e.g., Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation - 2+ years of experience with Python, including working knowledge of agent frameworks (e.g., LangGraph, LangChain, LlamaIndex, Semantic Kernel, or CrewAI)
Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.
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Yes. We’ve followed 15 other Lead AI/ML Engineer jobs there since April 2026. 10 came down, usually after about 18 days. 5 are still up.
If this one keeps the same pace, it may come down around November 22.
Large employers often post one title for several teams, so these can be separate openings.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
As a Lead AI/ML Engineer, you will play a key role in building and deploying production-grade Large Language Model (LLM) agents and Retrieval-Augmented Generation (RAG) pipelines that automate detection, triage, and remediation of platform and application issues.
Working at the intersection of machine learning engineering, system observability, and developer experience, you will design robust orchestration, guardrails, and evaluation frameworks to deliver high-impact AI capabilities.
You will partner closely with SRE, InfoSec, and platform teams to build scalable, secure, and responsible AI solutions integrated directly into existing software development workflows.
Primary Responsibilities:
Required Qualifications:
Preferred Qualifications:
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.
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Bangalore, Karnataka, India
- Build and deploy production LLM agents that automate detection, triage, and remediation of platform and application issues - Design and tune RAG pipelines over runbooks, incident history, logs, code, and internal documentation, including chunking strategy, embedding selection, vector store design, hybrid/semantic search, and reranking - Implement agent orchestration, including tool/function calling, multi-step planning, multi-agent handoffs, memory, and state management
No clear work-authorization passage found. Eligibility is unconfirmed.
