Senior AI Systems Architect - Enterprise Scale

Elevance Health

Louisville (KY)

Hybrid

USD 243,000 - 365,000

Full time

14 days+

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Benefits offered by this job

Hybrid work model

Equity stock purchase plan

401(k) contribution

Job summary

Elevance Health in Atlanta is seeking a Distinguished Engineer to lead the design, development, and deployment of large-scale AI systems driving enterprise-wide modernization. This role combines in-office collaboration 1-2 days per week with flexible virtual work to sustain productivity.

Ideal candidates will have 15+ years in software engineering, deep expertise in distributed systems, APIs, microservices, CI/CD, and cloud technologies, and a proven track record delivering production-grade

Qualifications

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.

Responsibilities

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.