Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 6 and day 69.
From 4,296 similar postings that came down. Coming down is not always a hire.
Senior AI/ML Engineer
Bangalore, Karnataka, India
Actively hiring, first seen by us today- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild and deploy production LLM agents for issue detection, triage, and remediation
Design and tune RAG pipelines over runbooks, incident history, logs, and code
Implement agent orchestration, tool calling, memory, and multi-agent handoffs
Build evaluation pipelines and quality metrics for agent and RAG behavior
Ship agent capabilities into EVA for developers to use in their workflow
From the employer’s posting
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: 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
Ship agent capabilities into EVA so developers consume them inside their existing workflow
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent experience
- 4+ years of software or machine learning engineering experience
- 2+ years hands-on building with LLMs, including prompt engineering, tool/function calling, and agent or multi-step orchestration
- Demonstrated experience designing and shipping RAG systems in production, including embeddings, vector databases (for example Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation
- Experience integrating third-party APIs and building backend services that run in production
- Experience with cloud platforms (Azure, AWS, or GCP), containers, and CI/CD pipelines
Qualification wording
Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent experience
4+ years of software or machine learning engineering experience
2+ years hands-on building with LLMs, including prompt engineering, tool/function calling, and agent or multi-step orchestration
Demonstrated experience designing and shipping RAG systems in production, including embeddings, vector databases (for example Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation
Experience integrating third-party APIs and building backend services that run in production
Experience with cloud platforms (Azure, AWS, or GCP), containers, and CI/CD pipelines
Education & alternatives
Required Qualifications: - Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent experience - 4+ years of software or machine learning engineering experience
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 4, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
UnitedHealth Group is hiring
159 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is steady
- Takes jobs down quickly
- 11% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Azure
- GCP
Where the posting names them
- Experience building LLM evaluation and testing workflows rather than relying on manual spot checks - Proficiency in Python, with working knowledge of agent frameworks (for example LangGraph, LangChain, LlamaIndex, Semantic Kernel, or CrewAI) - Proven ability to work across teams and translate operational pain points into technical requirements
- Experience integrating third-party APIs and building backend services that run in production - Experience with cloud platforms (Azure, AWS, or GCP), containers, and CI/CD pipelines - Experience building LLM evaluation and testing workflows rather than relying on manual spot checks
- 2+ years hands-on building with LLMs, including prompt engineering, tool/function calling, and agent or multi-step orchestration - Demonstrated experience designing and shipping RAG systems in production, including embeddings, vector databases (for example Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation - Experience integrating third-party APIs and building backend services that run in production
Your next step
Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.
Applying through Radancy (TalentBrew)
- Radancy (TalentBrew) runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.
Already applied? Track this application
Has UnitedHealth Group posted this job before?
Yes. We’ve followed 21 other Senior AI/ML Engineer jobs there since August 2026. 10 came down, usually after about 23 days. 11 are still up.
If this one keeps the same pace, it may come down around November 27.
Large employers often post one title for several teams, so these can be separate openings.
About the role
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.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
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.
Job description
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:
- 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 and semantic search, and reranking
- Implement agent orchestration: tool/function calling, multi-step planning, multi-agent handoffs, memory, and state management
- Integrate agents with observability and security platforms (alerting, logging, metrics, vulnerability and incident data) through APIs and MCP-style tool interfaces
- Build the supporting layer agents depend on: tool wrappers, guardrails, human-in-the-loop approval paths, and fallback behavior
- Own model and prompt engineering, including model selection, prompt and context optimization, output structuring, and cost/latency tuning; fine-tune or apply parameter-efficient techniques where warranted
- Build evaluation pipelines and define quality metrics for agent and RAG behavior (retrieval precision and recall, groundedness, hallucination and false-positive rate, escalation rate, MTTR impact) and iterate based on results
- Ship agent capabilities into EVA so developers consume them inside their existing workflow
- Partner with SRE, InfoSec, and platform teams to scope which classes of issues are safe to automate and which require human review
Contribute reusable patterns, components, and documentation for agent development across the Optum AI DLC
- 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 degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent experience
- 4+ years of software or machine learning engineering experience
- 2+ years hands-on building with LLMs, including prompt engineering, tool/function calling, and agent or multi-step orchestration
- Demonstrated experience designing and shipping RAG systems in production, including embeddings, vector databases (for example Azure AI Search, Pinecone, Milvus, pgvector, or FAISS), and retrieval evaluation
- Experience integrating third-party APIs and building backend services that run in production
- Experience with cloud platforms (Azure, AWS, or GCP), containers, and CI/CD pipelines
- Experience building LLM evaluation and testing workflows rather than relying on manual spot checks
- Proficiency in Python, with working knowledge of agent frameworks (for example LangGraph, LangChain, LlamaIndex, Semantic Kernel, or CrewAI)
- Proven ability to work across teams and translate operational pain points into technical requirements
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
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 and semantic search, and reranking - Implement agent orchestration: tool/function calling, multi-step planning, multi-agent handoffs, memory, and state management
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.