Architect

About Optum

Role Overview

Primary Responsibilities

• Design, build, deploy, and maintain machine learning and Generative AI solutions.
• Develop predictive, recommendation, NLP, deep learning, and LLM-based applications.
• Build data pipelines, feature engineering workflows, and model training frameworks.
• Implement RAG, vector search, prompt engineering, LLM evaluation, and foundation model deployment.
• Apply MLOps and LLMOps practices including CI/CD, testing, monitoring, and observability.
• Collaborate with technical and business stakeholders to translate requirements into scalable AI solutions.
• Improve model accuracy, latency, cost, reliability, security, and user experience.
• Provide technical leadership, mentoring, code reviews, and support for production AI systems.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field.
• 5+ years of professional software engineering, machine learning engineering, or AI development experience.
• 3+ years building and deploying machine learning solutions in production.
• Hands-on experience with LLMs, embeddings, prompt engineering, RAG, and vector databases.
• Experience with cloud-native solutions, Docker, Kubernetes, MLOps, and CI/CD automation.
• Strong understanding of machine learning fundamentals and model evaluation.
• Proficiency in Python, machine learning frameworks, SQL, data modeling, and large-scale data processing.
• Ability to communicate complex technical concepts to technical and non-technical audiences.

Preferred Qualifications

• Master's degree or higher in a related discipline.
• Healthcare experience in claims, pharmacy, clinical, provider, payer, or consumer health domains.
• Experience with HL7, FHIR, EHR integrations, Databricks, Snowflake, Spark, Kafka, or lakehouse architectures.
• Experience with MLflow, SageMaker, Azure ML, Vertex AI, or similar platforms.
• Experience with AI governance, model risk management, Responsible AI, agentic architectures, or multi-agent systems.
• Familiarity with vector databases and frameworks such as LangChain, LlamaIndex, Semantic Kernel, or AutoGen.

Governance and Compliance

• Ensure AI solutions follow Responsible AI principles, data governance standards, HIPAA requirements, and enterprise security controls.
• Preferred experience includes healthcare privacy, compliance, and security frameworks such as HIPAA and HITRUST.