Reads like an AI Engineer role: building products on existing AI models.
Bangalore, Karnataka, India
Actively hiring, first seen by us 9 days agoBuild and deploy production LLM agents that automate detection, triage, and remediation
Design and tune RAG pipelines over runbooks, incident history, logs, and code
Implement agent orchestration, tool calling, memory, and human-in-the-loop approval paths
Build evaluation pipelines and quality metrics for agent and RAG behavior
Integrate agents with observability and security platforms via APIs and MCP tools
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
Implement agent orchestration, including tool/function calling, multi-step planning, multi-agent handoffs, memory, and state management
Build evaluation pipelines and define quality metrics for agent and RAG behavior
Integrate agents with observability and security platforms (alerting, logging, metrics, vulnerability, and incident data) through APIs and Model Context Protocol (MCP) tool interfaces
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 9 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 9
Similar jobs usually come down between day 4 and day 77.
At UnitedHealth Group, jobs usually come down by about day 13.
From 51 similar postings that came down, and 942 of UnitedHealth Group’s. Coming down is not always a hire.
167 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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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 9 other Lead AI/ML Engineer jobs there since April 2026. 4 came down, usually after about 12 days. 5 are still up.
If this one keeps the same pace, it may come down around November 16.
Large employers often post one title for several teams, so these can be separate openings.
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
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.