Optum is seeking a Lead Software Engineer to design, build, and scale next generation agentic AI systems that enhance healthcare delivery and operations. This individual contributor role combines hands-on architecture, development, and deployment of sophisticated AI-powered solutions, with a focus on reliability, compliance, and close collaboration across clinical and technical teams. The position is based in Richardson, TX with remote options, offering a yearly salary range of USD 112,700 to 193,200.
Responsibilities
- Architect and implement multi-agent workflows where large language models plan tasks, break them down, call tools and APIs, and fuse results from diverse data sources and services.
- Develop retrieval augmented generation and hybrid search pipelines to enable robust question answering over clinical and operational data.
- Design, implement, test, document, and maintain scalable big data and cloud-based solutions with strong quality standards.
- Create scalable microservices and APIs to integrate agent capabilities into clinician tools and internal applications.
- Produce prototypes and proofs-of-concept and conduct design and code reviews to reduce delivery risk and uplift engineering quality.
- Leverage and tailor LLMs through prompt engineering, grounding, guardrails, and domain adaptation for healthcare terminology and tasks.
- Develop intelligent frameworks and fine-tune models to meet compliance, accuracy, and ethical requirements.
- Establish evaluation frameworks combining automated and human-in-the-loop assessments to measure faithfulness, usefulness, bias, toxicity, privacy leakage, and overall quality.
- Collaborate with data engineering to build feature stores and retrieval stores, embeddings pipelines, and ETL/ELT jobs on Spark/Databricks; design analytics models and rules engines.
- Define and develop enterprise APIs and improve data access patterns for low-latency inference across the organization.
- Own MLOps/LLMOps including CI/CD for models and prompts, automated tests, versioning, lineage, rollback, and blue/green or canary releases.
- Instrument SLOs/SLIs and cost KPIs with dashboards and alerts, focusing on latency, availability, hallucination/defect rate, tokens, and GPU hours.
- Lead production deployments on internal platforms such as UAIS, ensuring observability, reliability, and cost controls.
- Champion HIPAA and regulated industry controls by integrating access controls, PHI/PPI safeguards, data minimization, encryption, and auditability.
- Collaborate with legal, compliance, and clinical safety to operationalize Responsible AI principles.
- Analyze customer requirements and contribute to defining product technical architecture and delivery roadmaps.
- Provide effort estimates and resource planning inputs while partnering with QA, architecture, and peer teams.
- Write technical documentation, support production, mentor engineers, and maintain current skills through continuous learning.
Requirements
- Bachelor's degree in Engineering, Computer Science, IT, or related field.
- 10+ years of total technology experience.
- 8+ years hands-on software development, data engineering, or analytics with solid AI/ML delivery (Azure preferred) using Scala, Python, and PySpark.
- 4+ years hands-on with Databricks.
- 4+ years with ADF or Airflow for orchestration and scaling.
- 4+ years with big data and streaming technologies (Hadoop, MapReduce/HDFS, Spark, Kafka); Docker and Kubernetes.
- 4+ years working with MySQL and NoSQL databases.
- 4+ years in Agile/Scrum environments with GitHub, Jenkins CI/CD, and JUnit; strong coding standards and code reviews.
- 2+ years with LLMs and GenAI ecosystems (Langchain, LangGraph, RAG, Vector DB, Azure OpenAI, MCP Server, Agents, LangFuse).
- 2+ years of container experience (Docker/Kubernetes).
- 1+ years building services or full-stack applications (e.g., FastAPI/Flask, Node.js, React/Angular, TypeScript, HTML/CSS).
Technologies
Scala, Python, PySpark, Databricks, ADF/Airflow, Hadoop, MapReduce/HDFS, Spark, Kafka, Docker, Kubernetes, MySQL, NoSQL databases, GitHub, Jenkins, JUnit, Langchain, LangGraph, RAG, Vector DB, Azure OpenAI, MCP Server, Agents, LangFuse, FastAPI, Flask, Node.js, React, Angular, TypeScript, HTML/CSS, UAIS, Azure.
Benefits
- Comprehensive benefits package
- Incentive and recognition programs
- Employee stock purchase plan
- 401(k) contribution
Preferred Qualifications
- Healthcare experience and familiarity with clinical datasets
- Experience in regulated industries with knowledge of ethical AI/ML practices and compliance requirements
- Service-oriented architecture and enterprise integration concepts
- Publications, patents, or notable open-source contributions
- Strong analytical, problem-solving, and communication skills
Application Deadline
This job posting remains open for a minimum of two business days or until a sufficient candidate pool is identified. The posting may close earlier if a high volume of applications is received.
