Lead AI Engineer - Remote

Salary: $112,700 - 193,200 per year Requirements:

• We require a bachelors degree in Engineering, Computer Science, IT, or a related discipline.
• We expect at least 10 years of overall technology experience.
• We need 8+ years of hands-on experience in software development, data engineering, or analytics, with strong AI/ML delivery experience; Azure is preferred, along with Scala, Python, and PySpark.
• We require 4+ years of practical experience with Databricks.
• We require 4+ years of experience with orchestration and scaling tools such as ADF or Airflow.
• We require 4+ years of experience with big data and streaming technologies, including Hadoop, MapReduce/HDFS, Spark, Kafka, Docker, and Kubernetes.
• We require 4+ years of experience working with MySQL and NoSQL databases.
• We require 4+ years of experience in Agile/Scrum environments, GitHub, Jenkins CI/CD, JUnit, and strong coding and code review practices.
• We need 2+ years of experience with LLMs and GenAI tools such as LangChain, LangGraph, RAG, vector databases, Azure OpenAI, MCP Server, agents, and LangFuse.
• We require 2+ years of experience with container technologies, including Docker and Kubernetes.
• We require 1+ year of experience building services or full-stack applications using tools such as FastAPI, Flask, Node.js, React, Angular, TypeScript, and HTML/CSS.
• We prefer healthcare experience and familiarity with clinical datasets.
• We prefer experience in regulated industries, including knowledge of ethical AI/ML practices and compliance requirements.
• We prefer understanding of SOA and enterprise integration concepts.
• We value publications, patents, or noteworthy open-source contributions.
• We look for strong analytical thinking, problem-solving ability, and communication skills.

• We design and implement multi-agent AI workflows where LLMs plan tasks, call tools and APIs, and combine results from multiple data sources and services.
• We build retrieval-augmented generation and hybrid search pipelines to support reliable question answering over clinical and operational data.
• We design, code, test, document, and maintain scalable, high-quality Big Data and cloud solutions.
• We develop microservices and APIs that embed agent capabilities into clinician tools and internal applications.
• We create prototypes and proof-of-concepts, and we conduct design and code reviews to reduce delivery risk and improve engineering quality.
• We apply prompt engineering, grounding, guardrails, and domain adaptation for healthcare terminology and use cases.
• We design intelligent frameworks and fine-tune models to support compliance, accuracy, and ethical standards.
• We build evaluation frameworks, combining automated and human-in-the-loop methods, to assess faithfulness, usefulness, bias, toxicity, privacy leakage, and overall quality.
• We work with data engineering to build feature and retrieval stores, embedding pipelines, and ETL/ELT jobs on Spark and Databricks.
• We define and develop APIs for enterprise integrations and improve data access patterns for low-latency inference.
• We own MLOps and LLMOps practices, including CI/CD for models and prompts, automated testing, versioning, lineage, rollback, and blue/green or canary releases.
• We monitor SLOs, SLIs, and cost metrics through dashboards and alerts, tracking latency, availability, defect rates, token usage, and GPU hours.
• We lead production deployments on internal platforms with strong observability, reliability, and cost controls.
• We champion HIPAA and regulated-environment controls, including access management, PHI/PPI safeguards, data minimization, encryption, and auditability.
• We collaborate with legal, compliance, and clinical safety teams to operationalize Responsible AI principles.
• We analyze customer needs and help define technical architecture and delivery roadmaps.
• We provide effort estimates and support resource planning, while partnering with QA, architecture, and peer teams.
• We write technical documentation, support production systems, mentor engineers, and keep our skills current through continuous learning.

• Agentic AI
• AI
• Airflow
• Angular
• Azure
• Big Data
• CI/CD
• Cloud
• CSS
• Databricks
• Docker
• ETL
• FastAPI
• Flask
• Flow
• GitHub
• Hadoop
• Support
• JUnit
• Jenkins
• Kafka
• Kubernetes
• Langfuse
• MCP
• MLOps
• MySQL
• NoSQL
• Python
• PySpark
• RAG
• React
• Scala
• Spark
• TypeScript
• microservices
• NodeJS
• Architect
• Security

More:

We are Optum Insight, and we are improving the flow of health data and information to create a more connected healthcare system. Our technology and industry expertise help organizations reduce costs, strengthen risk management, improve quality, and support revenue growth. This Lead Software Engineer role is a hands-on individual contributor position focused on designing and scaling next-generation agentic AI solutions for healthcare delivery and operations. We offer remote work flexibility from anywhere in the U.S., with a requirement for Minneapolis or Washington, D.C. hires to work in the office at least four days per week. We also provide a comprehensive benefits package, incentive and recognition programs, equity stock purchase, and 401(k) contribution, with salary ranging from $112,700 to $193,200 annually depending on full-time status and other factors. We are committed to helping people live healthier lives, advancing equitable care, and maintaining an inclusive, drug-free workplace.

last updated 33 week of 2026