Elevance Health
Mason, Ohio
Distinguished Engineer Please note: This position is not eligible for current or future visa sponsorship Hybrid: This role requires associates to be in-office 3 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within a commuting distance from an office. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. The Distinguished Engineer is responsible for leading the design, development, and deployment of large-scale, production-grade artificial intelligence (AI) systems and platforms that enable enterprise-wide innovation and modernization. How you will make an impact: Architect and deliver scalable, resilient AI solutions leveraging technologies such as agentic systems, large language models (LLMs), distributed systems, and event-driven architectures. Define enterprise-wide technical direction, including architecture patterns, integration standards, and reusable platform capabilities. Lead AI-driven modernization of legacy systems through automated code transformation, service decomposition, and continuous optimization. Design and implement AI-enabled software development lifecycle (SDLC) practices to improve engineering velocity and quality. Establish technical standards, governance frameworks, and best practices for AI systems, including monitoring, evaluation, and responsible AI. Partner with engineering teams and stakeholders to enable adoption of AI-assisted development and drive continuous improvement in system performance and productivity. Provide technical leadership and mentorship while influencing enterprise technology decisions through deep expertise and hands-on engineering. Minimum Requirements: Requires a bachelor's degree in information technology, Computer Science, Engineering, or a related field and a minimum of 15 years of experience in software engineering, including experience leading, designing, implementing, and operating distributed systems and large-scale architectures, or any combination of education and experience which would provide an equivalent background. Experience designing, developing, and maintaining software solutions using Python, Java, or comparable object-oriented programming languages also required, as well as experience designing and implementing APIs, microservices, and event-driven architectures, and applying cloud, CI/CD, and DevOps practices. Preferred Skills, Capabilities, and Experiences: For this role, we're seeking a distinguished technical leader who combines enterprise-level strategic thinking, deep business understanding, and exceptional hands-on software engineering capabilities. The ideal candidate must demonstrate a proven track record of personally designing, building, and delivering production-grade solutions while influencing enterprise technology strategy, developing technical talent, and driving measurable business outcomes. AI Expertise and Strategic Thinking: Deep understanding of AI, generative AI, agentic systems, LLMs, intelligent automation, and modern data architectures. Experience designing and operating large-scale agentic or autonomous systems in production. Expertise with: Agent frameworks (LangChain, Semantic Kernel, AutoGen, etc.) Vector databases and retrieval-augmented generation (RAG) LLMOps, evaluation, and monitoring frameworks Experience with multi-agent coordination, planning, and memory architecture. Enterprise Data Architecture and Strategy: Deep expertise in cloud-native enterprise data platforms, lakehouse and analytical architectures, governed data products, data integration, interoperability, metadata management, data quality, lineage, and secure access across complex domains. Semantic, Context, and Knowledge Architecture: Hands-on experience designing semantic and context layers, business vocabularies and metrics, ontologies, knowledge graphs, entity relationships and resolution, and reusable knowledge representations that connect enterprise data to AI. Familiarity with RDF/OWL, SPARQL, SHACL, graph databases, and semantic modeling is highly valued. AI on Enterprise Data and Conversational Analytics: Experience implementing trustworthy natural-language analytics, text-to-SQL with governed semantic definitions, RAG/GraphRAG, semantic retrieval, context engineering, and AI agents that query, reason over, and act on enterprise data. Demonstrated attention to provenance, authorization, evaluation, explainability, and numerical accuracy. Healthcare Data and Decision Intelligence: Ability to apply enterprise data, semantics, analytics, ML, and AI to provider data and analytics, utilization management, prior authorization, clinical interoperability (FHIR/HL7), medical cost management, shift-left payment integrity, value-based care, employer analytics, claims, and care management. Experience connecting clinical, member, provider, benefit, contract, and policy data is especially valuable.
Distinguished Engineer Please note: This position is not eligible for current or future visa sponsorship Hybrid: This role requires associates to be in-office 3 days per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Alternate locations may be considered if candidates reside within a commuting distance from an office. Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law. The Distinguished Engineer is responsible for leading the design, development, and deployment of large-scale, production-grade artificial intelligence (AI) systems and platforms that enable enterprise-wide innovation and modernization. How you will make an impact: Architect and deliver scalable, resilient AI solutions leveraging technologies such as agentic systems, large language models (LLMs), distributed systems, and event-driven architectures. Define enterprise-wide technical direction, including architecture patterns, integration standards, and reusable platform capabilities. Lead AI-driven modernization of legacy systems through automated code transformation, service decomposition, and continuous optimization. Design and implement AI-enabled software development lifecycle (SDLC) practices to improve engineering velocity and quality. Establish technical standards, governance frameworks, and best practices for AI systems, including monitoring, evaluation, and responsible AI. Partner with engineering teams and stakeholders to enable adoption of AI-assisted development and drive continuous improvement in system performance and productivity. Provide technical leadership and mentorship while influencing enterprise technology decisions through deep expertise and hands-on engineering. Minimum Requirements: Requires a bachelor's degree in information technology, Computer Science, Engineering, or a related field and a minimum of 15 years of experience in software engineering, including experience leading, designing, implementing, and operating distributed systems and large-scale architectures, or any combination of education and experience which would provide an equivalent background. Experience designing, developing, and maintaining software solutions using Python, Java, or comparable object-oriented programming languages also required, as well as experience designing and implementing APIs, microservices, and event-driven architectures, and applying cloud, CI/CD, and DevOps practices. Preferred Skills, Capabilities, and Experiences: For this role, we're seeking a distinguished technical leader who combines enterprise-level strategic thinking, deep business understanding, and exceptional hands-on software engineering capabilities. The ideal candidate must demonstrate a proven track record of personally designing, building, and delivering production-grade solutions while influencing enterprise technology strategy, developing technical talent, and driving measurable business outcomes. AI Expertise and Strategic Thinking: Deep understanding of AI, generative AI, agentic systems, LLMs, intelligent automation, and modern data architectures. Experience designing and operating large-scale agentic or autonomous systems in production. Expertise with: Agent frameworks (LangChain, Semantic Kernel, AutoGen, etc.) Vector databases and retrieval-augmented generation (RAG) LLMOps, evaluation, and monitoring frameworks Experience with multi-agent coordination, planning, and memory architecture. Enterprise Data Architecture and Strategy: Deep expertise in cloud-native enterprise data platforms, lakehouse and analytical architectures, governed data products, data integration, interoperability, metadata management, data quality, lineage, and secure access across complex domains. Semantic, Context, and Knowledge Architecture: Hands-on experience designing semantic and context layers, business vocabularies and metrics, ontologies, knowledge graphs, entity relationships and resolution, and reusable knowledge representations that connect enterprise data to AI. Familiarity with RDF/OWL, SPARQL, SHACL, graph databases, and semantic modeling is highly valued. AI on Enterprise Data and Conversational Analytics: Experience implementing trustworthy natural-language analytics, text-to-SQL with governed semantic definitions, RAG/GraphRAG, semantic retrieval, context engineering, and AI agents that query, reason over, and act on enterprise data. Demonstrated attention to provenance, authorization, evaluation, explainability, and numerical accuracy. Healthcare Data and Decision Intelligence: Ability to apply enterprise data, semantics, analytics, ML, and AI to provider data and analytics, utilization management, prior authorization, clinical interoperability (FHIR/HL7), medical cost management, shift-left payment integrity, value-based care, employer analytics, claims, and care management. Experience connecting clinical, member, provider, benefit, contract, and policy data is especially valuable.