Distinguished Engineer - Responsible AI

Elevance Health•Chicago, IL

1d•$254,584 - $381,876•Hybrid

About The Position

The Distinguished Engineer - Responsible AI leads the design, development, governance, and deployment of enterprise-scale AI systems with Responsible AI at the core. This role sets the technical strategy, architecture patterns, and engineering practices needed to build AI solutions that are scalable, secure, reliable, explainable, compliant, and aligned with enterprise Responsible AI principles. As a senior technical leader, the Distinguished Engineer - RAI partners with engineering, data science, security, legal, compliance, product, and business teams to ensure AI systems include appropriate controls for fairness, transparency, privacy, safety, robustness, accountability, and human oversight.

Requirements

Requires a Bachelor’s degree in Computer Science, Information Technology, or related field and a minimum of 15 years of experience in software engineering, expertise in distributed systems and large-scale architecture, or any combination of education and experience, which would provide an equivalent background.
Experience delivering production-grade AI/ML systems at scale, building agentic systems or complex LLM-based applications, modernizing large, complex legacy systems, and delivering high-quality systems also required.
Strong programming expertise in Python, Java, or similar required.
Experience with APIs, microservices, and event-driven architectures, cloud platforms, and CI/CD and DevOps practices required.

Nice To Haves

Ability to translate policy, risk, compliance, legal, privacy, and security requirements into practical engineering patterns and platform capabilities.
Experience implementing AI governance and control frameworks, including model evaluation, validation, documentation, monitoring, auditability, model risk management, and regulatory compliance.
Demonstrated ability to influence senior technical and business stakeholders, establish enterprise standards, mentor engineering leaders, and drive adoption of modern Responsible AI practices.
Hands-on experience with LLM evaluation, prompt safety, hallucination mitigation, content safety, toxicity detection, jailbreak resistance, red-teaming, guardrails, and AI observability.
Strong programming expertise in Python, Java, or similar.
Deep experience with APIs, microservices, and event-driven architectures, cloud platforms, and CI/CD and DevOps practices.

Responsibilities

Define enterprise-wide technical direction for Responsible AI engineering, including architecture patterns, integration standards, model risk controls, evaluation frameworks, guardrails, observability, and reusable platform capabilities.
Partner with engineering, data science, legal, compliance, security, privacy, and risk teams to translate Responsible AI principles, regulatory expectations, and enterprise policies into practical technical controls.
Develop reusable Responsible AI platform services, reference architectures, tooling, and implementation patterns to accelerate safe and consistent adoption of AI across the enterprise.
Architect and deliver scalable, resilient AI solutions leveraging technologies such as agentic systems, large language models (LLMs), distributed systems, and event-driven architectures.
Define and operationalize metrics for AI system quality, trustworthiness, safety, fairness, reliability, performance, and business impact.
Lead AI-driven modernization of legacy systems through automated code transformation, service decomposition, and continuous optimization.
Establish technical standards, governance frameworks, and best practices for AI systems, including monitoring, evaluation, and responsible AI.
Provide technical leadership and mentorship while influencing enterprise technology decisions through deep expertise and hands-on engineering.