AI-Native Engineering Lead: Production Systems & AI

Accenture PLC; Raleigh (NC); On-site; USD 120,000 - 260,000; Full time

Benefits offered by this job

Medical, dental, vision, life

401(k) plan

Paid holidays and paid time off

Job summary

Accenture is seeking a senior software engineering leader to design and operate end‑to‑end production systems spanning frontend, backend, data, and AI components. You will own architectural decisions, partner with client tech leaders, and drive production readiness across cloud platforms and DevSecOps workflows.

You will shape AI‑native and agentic engineering practices, build scalable data pipelines, and lead cross‑functional teams while delivering measurable outcomes in complex enterprise

Qualifications

• Minimum of 5 years of professional software engineering experience building and operating production systems.
• Minimum of 5 years of hands‑on experience spanning multiple layers of the stack, including front end or API through services, integration, persistence, and asynchronous processing.
• Minimum of 5 years of programming experience in at least one major language such as Java, Python, Go, TypeScript/JavaScript, or C#.
• Minimum of 5 years of hands‑on production experience with a major cloud platform (AWS, Azure, or GCP), including containers and orchestration (Docker, Kubernetes) and infrastructure as code (Terraform, Helm, or equivalent).
• Minimum of 5 years of experience designing and operating CI/CD pipelines through to production, including automated testing and integrated security controls.
• Minimum of 1 years of hands‑on experience designing, building, and deploying AI‑enabled or agentic systems in production or near‑production environments, including model integration, tool use, retrieval, context engineering, orchestration, and evaluation.
• Minimum of 1 years of experience applying AI‑native engineering tools and workflows to day‑to‑day software development, including code generation, automated testing, debugging, modernization, and documentation.
• Minimum of 5 years of experience leading engineering teams or significant technical workstreams, including leading client‑facing technical discussions, workshops, or delivery sessions under ambiguity.
• Bachelor's degree in Computer Science, Engineering or equivalent OR equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)

Responsibilities

• Design and build production systems across front end, APIs, backend services, integration, data, infrastructure, and AI components, making architectural decisions across all of these concerns together.
• Diagnose production issues wherever they live: application code, networks, infrastructure, identity, data, or AI workloads.
• Design and deploy workloads using containers, Kubernetes, serverless, managed cloud services, and infrastructure as code (Terraform, Helm, or equivalent), building for elasticity, resilience, and recoverability.
• Use the native capabilities of AWS, Azure, or GCP, including cloud networking, compute, storage, identity, secrets, service communication, and workload isolation.
• Build the automated path from commit to production: CI/CD, automated testing, security scanning, artifact management, infrastructure deployment, policy enforcement, and release controls.
• Apply secure‑by‑design practices (identity, least privilege, secrets, encryption, dependency and supply‑chain security), instrument logs, metrics, traces, and SLOs, and lead incident response and root‑cause analysis.
• Engineer Data and Context
• Design and implement the transactional, streaming, analytical, and unstructured data flows the solution needs, across relational and non‑relational stores, object storage, event platforms, and pipelines.
• Design the data and context architecture AI systems depend on, including retrieval, embeddings, metadata, knowledge sources, and context management, with quality, lineage, access, retention, and privacy engineered in.
• Build AI capabilities using frontier and enterprise models, integrated into live enterprise systems and production workflows.
• Build agentic systems with tools, memory, context, planning, human intervention, and policy‑controlled execution, including evaluation frameworks and production safeguards that keep probabilistic components trustworthy.

Skills

Software engineering

Cloud platforms (AWS/Azure/GCP)

CI/CD pipelines

DevSecOps

AI/agentic systems

Leadership / cross-functional teams

Education

Bachelor's degree in Computer Science, Engineering or equivalent OR equivalent (minimum 12 years) work experience

Tools

Docker

Kubernetes

Terraform

Helm

Job description

Accenture is seeking a senior software engineering leader to design and operate end‑to‑end production systems spanning frontend, backend, data, and AI components. You will own architectural decisions, partner with client tech leaders, and drive production readiness across cloud platforms and DevSecOps workflows.

You will shape AI‑native and agentic engineering practices, build scalable data pipelines, and lead cross‑functional teams while delivering measurable outcomes in complex enterprise