AI Native Software Engineering Manager - Reinvention Center
Accenture
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Job summary
Accenture in Columbus, OH is seeking a senior software engineer to design and operate complex production systems across front end, APIs, data, and AI components. You will own architecture through production, ship scalable solutions, and apply secure-by-design practices in a cloud-native environment.
You will lead multidisciplinary teams, craft architectural direction, and stay hands-on while mentoring others. A Bachelor's degree or equivalent and 8+ years of experience are required.
Qualifications
- 8+ years of professional software engineering experience.
- 5+ years across stack layers: front end to data and AI.
- 3+ years with a major cloud platform (AWS, Azure, or GCP) including containers.
- 3+ years CI/CD pipelines to production.
- 1+ year AI-enabled or agentic systems in production.
- 3+ years leading engineering teams or significant technical workstreams.
- Bachelor's degree or equivalent (minimum 12 years) work experience.
Responsibilities
- Lead multidisciplinary teams across software, cloud, platform, security, data, and AI engineering; set engineering standards and develop the engineers around you.
- Turn ambiguous requirements into architectures, executable increments, and measurable outcomes, then get them into production.
- Design and operate production systems across front end, APIs, backend services, data, and AI components.
- Build agentic AI capabilities with robust governance, testing, and observability.
Skills
Education
Tools
Job description
The Advanced Technology Centers (ATCs) is the engine for reinvention in our clients’ transformation journey. Powered by more than 255,000* people across 24 countries, ATCs will provide our clients with seamless access to industry insights and innovative technology solutions.
The Advanced Technology Centers (ATCs) is the engine for reinvention in our clients’ transformation journey. Powered by more than 255,000* people across 24 countries, ATCs will provide our clients with seamless access to industry insights and innovative technology solutions.
The Advanced Technology Centers (ATCs) make tremendous impact in solving our clients’ business problems leveraging Innovation, Intelligence, Industry insights, new IT and new technology skills. Now, with the global environment changing at a faster pace, our clients are facing unprecedented challenges, and they need us more than ever before. As a Network, ATCs are positioned to unlock greater opportunities and exponential value for our clients.
For our clients, the Network provides the strength of our geographic diversity, greater resilience, and seamless access to the deepest industry knowledge, the latest in Gen AI solutions, and tech expertise from around the world.
For our people, it brings an opportunity to shape truly boundaryless career paths in a highly collaborative team of experts where they can learn from each other and solve the world’s most complex client challenges.
A senior engineer who can build and operate an entire production system. You work across application and product engineering, APIs and services, data, cloud infrastructure, DevSecOps, security, observability, and AI, and you are comfortable being accountable for all of it. You take an ambiguous business or engineering problem and own the technical solution from architecture through production. You are equally credible designing a distributed system, provisioning the infrastructure it runs on, building the pipeline that ships it, and designing the AI and agentic capabilities that operate inside it.
You also engineer with AI. It is part of how you build software: how you generate, test, review, modernize, document, and operate it. You can demonstrate the measurable difference it makes to your own delivery.
You'll shape how enterprises adopt AI-native engineering by leading multidisciplinary teams and setting technical direction, while staying hands‑on enough to inspect, challenge, prototype, and debug the implementation yourself.
You’ll partner directly with client technology leaders, acting as both engineer and trusted advisor. You’ll turn ambiguous requirements into architectures, executable increments, and measurable outcomes, then get them into production. Often these are net-new platforms that have to be stitched into a client's existing estate alongside our ecosystem partners.
- 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.
- 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.
- Design and implement AI capabilities using frontier and enterprise models (OpenAI, Anthropic, Microsoft, Google, AWS, and others), integrated into live enterprise systems and production workflows.
- Build agentic systems with tools, memory, context, planning, human intervention, and policy-controlled execution, together with the evaluation frameworks, AI observability, and production safeguards that keep probabilistic components trustworthy inside deterministic enterprise systems.
- Use AI-native development techniques throughout the lifecycle, including code generation, testing, debugging, modernization, documentation, analysis, and operations, and design engineering workflows in which agents can safely perform bounded development and operational tasks.
- Continuously identify where AI materially improves engineering throughput, quality, or system operations, and establish the context, tools, permissions, evaluations, and human controls that make it safe.
- Lead multidisciplinary teams spanning software, cloud, platform, security, data, and AI engineering; set engineering standards and develop the engineers around you.
- Facilitate architecture and engineering sessions with senior client technologists, and communicate trade-offs, risks, and recommendations clearly to both technical and executive audiences.
- Convert lessons from delivery and production failures into reusable patterns, tooling, automation, and standards that influence internal assets and client roadmaps.
- Contribute to internal communities of practice around AI-native and agentic engineering.
- Minimum of 8 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 3 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 3 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 3 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 OR equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)
- Built multi‑agent orchestrations using frameworks such as LangGraph, Crew AI, the Claude Agent SDK, or the OpenAI SDK.
- A public repository, portfolio, or open-source contribution featuring agents, tools, or plugins you built yourself.
- Designed model and provider abstraction layers covering routing, fallback, latency, throughput, and cost management across multiple AI providers.
- Defined enterprise‑grade architectures for compound AI systems, orchestration frameworks, or agent registry and stream‑based architectures.
- Relevant cloud, security, or AI certifications.
- Delivered AI-native solutions across more than one industry (for example financial services, healthcare, retail), adapting workflows to domain‑specific processes and constraints.
- Experience applying AI-assisted engineering to modernize an existing legacy estate.
- Driven execution across multiple concurrent workstreams while holding quality, delivery, and alignment with client outcomes.
Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long‑term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here: U.S. Employee Benefits | Accenture
Role Location Annual Salary Range
California $94,400 to $316,300
Colorado $94,400 to $273,200
Connecticut $94,400 to $273,200
District of Columbia $100,500 to $291,000
Illinois $87,400 to $273,200
Maine $80,400 to $232,800
Maryland $94,400 to $273,200
Massachusetts $94,400 to $291,000
Minnesota $94,400 to $273,200
New York $87,400 to $316,300
New Jersey $100,500 to $316,300
Ohio $87,400 to $253,000
Virginia $87,400 to $291,000
Washington $100,500 to $291,000
Columbus, OH
Atlanta, GA
Chesterbrook, PA
Dallas, TX
Houston, TX
St. Petersburg, FL
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We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other.
We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work.
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