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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - AI/ML - **Company:** Unitedhealth Group Inc - **Location:** Washington, DC, United States (Remote available) - **Salary:** $98,500.0 - $176,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Cloud Engineering, Continuous Integration, Data Cleansing, DevOps, Github, Apache Hadoop, Python (Programming Language), Machine Learning, Scrum Methodology, Tensorflow, Standard Sql, SQL Databases, Transact-SQL, Google Cloud, Chatbots, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Snowflake, Prompt Engineering, Apache Spark, Deep Learning, Generative AI, Git, Pandas, Containerization, Data Lakes, AI Platforms, Pyspark, HuggingFace, Apache Kafka, Data Management, Machine Learning Operations, Gsuite, Virtual Agents, Restful APIs, GPT, Software Version Control, Data Pipelines, Docker, Databricks - **Published:** June 12, 2026 - **Apply:** https://www.dice.com/job-detail/a327aa95-8c5c-4467-bcf7-ff3f6087f84d ## About the Role * Bachelor's degree in CS or IT related field * 5+ years of hands-on experience in AI/ML techniques like Prompt Engineering, RAG (Retrieval Augmented Generation) and Agentic AI * 5+ years of experience and strong expertise in Python, PySpark, T-SQL, SQL, and big data technologies (Hadoop, Spark) * 2+ years of experience in statistics, data modeling, and simulation * 1+ years of experience with Generative AI frameworks/architectures (LangChain, HuggingFace, OpenAI APIs) * 1+ years of experience with any one of the cloud technologies: Azure (Databricks, ML Studio), AWS Bedrock, Azure Foundry, Kafka, Google Cloud Platform, and cloud-native AI services * 1+ years of experience with CI/CD pipelines, GitHub Actions, and containerization tools * 1+ years of experience with LLM security, prompt engineering, and responsible AI practices, * Experience with LLMs (GPT, Gemini, LLaMA) and prompt-based learning * Knowledge of Kafka, TensorFlow, and advanced deep learning architectures (CNNs, Autoencoders) * Strong understanding of Agile methodologies and DevOps practices * Internal Data management and big data handling experience * Excellent problem-solving skills and ability to handle ambiguity *All Telecommuters will be required to adhere to UnitedHealth Group's Telecommuter Policy. ## Description We are seeking a highly skilled and motivated AI/ML Engineer to lead innovations in claims adjudication through advanced Generative AI solutions. This role emphasizes Large Language Models (LLMs), agentic frameworks, and prompt engineering to automate complex workflows. You will design and deploy secure, scalable, and responsible AI systems while collaborating across teams to deliver measurable impact. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office for a minimum of four days per week. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges., * Design, develop, and deploy AI/ML and Generative AI models for predictive, prescriptive, and generative analytics across healthcare datasets * Implement advanced architectures including LLMs (GPT, Gemini, LLaMA), Retrieval-Augmented Generation (RAG), and Agentic Frameworks * Build and optimize end-to-end pipelines using Python (Sci-kit Learn, Pandas, Flask, LangChain), PySpark, T-SQL and SQL * Develop and fine-tune multiple GenAI models for NLP, summarization, prompt engineering, and conversational AI * Apply MLOps best practices: model versioning, drift analysis, quantization, MLFlow, containerization with Docker, and CI/CD pipelines * Work with cloud platforms: Azure (Databricks, ML Studio, Data Factory, Data Lake, Delta Tables), AWS, and Google Cloud Platform for scalable deployments * Integrate data warehousing solutions like Snowflake and manage large-scale data pipelines. * Collaborate in an Agile environment, participate in sprint planning, and maintain code repositories using GitHub/Git * Ensure compliance with security and governance standards for healthcare data * Coach and mentor junior team members. * Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI Technical Skillset AI/ML Foundations * Design and implement machine learning and deep learning models for classification, NLP tasks * Build and maintain end-to-end ML pipelines including data preprocessing, model training, evaluation, and deployment Generative AI & LLM Engineering * Develop and fine-tune LLM-based applications using LangChain, LangGraph, and other GenAI frameworks * Build Multi Agentic workflows and RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases * Leverage AWS Bedrock and Google Vertex AI for scalable and production-grade GenAI deployments LLM Security & Responsible AI * Implement guardrails to prevent prompt injections, reduce hallucinations, and ensure safe model outputs * Apply best practices for LLM security, including output moderation, access control, and auditability * Ensure compliance with Responsible AI principles-fairness, transparency, and explainability Cloud-Native AI Development * Deploy and manage GenAI solutions on AWS and Google Suite, utilizing services like Bedrock, SageMaker, Vertex AI * Integrate LLMs with enterprise systems using REST APIs, SDKs, and orchestration tools Collaboration & Mentorship * Work closely with product managers, data scientists, and platform teams to translate business needs into GenAI solutions * Mentor junior engineers and contribute to internal knowledge-sharing initiatives You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear directions on what it takes to succeed in your role as well as provide development for other roles you may be interested in. ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) - [AI in High-Stakes Industries: Lessons Learned](https://www.wearedevelopers.com/videos/100253-ai-in-high-stakes-industries-lessons-learned) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Got AI ideas but no money? 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