AI Native Engineer Senior Analyst - Reinvention Center

Accenture•Columbus, OH

3d•$48,838 - $169,894•Hybrid

About The Position

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. An AI Native Engineer with experience building cloud-native solutions, and deep expertise in designing and deploying agentic systems, especially for enterprise environments. A critical thinker that thrives in ambiguity, delivering concrete results by designing, building, and running custom AI agents that augment workflows and scale across modern infrastructure. This role will help shape the playbook for how enterprises adopt and scale AI-native engineering globally. You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely net new platforms and systems that need to be stitched together in our clients' environments alongside our Ecosystem partners.

Requirements

Minimum of 2 years of engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
Minimum of 1 year of hands-on experience designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production or near-production environments.
Minimum of 1 year of experience with modern AI platforms — OpenAI, Claude, Vertex AI, or open-source models — including building or using abstraction layers for multi-provider pipelines.
Minimum of 3 years strong Python, Java or equivalent experience building 12 factor applications + Infrastructure as Code (Terraform, Helm).
Minimum of 3 years of experience in client-facing communication and collaboration, including leading 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)

Nice To Haves

Relevant AI certifications or agentic tooling experience are a plus.
Served as an Agentic / AI Engineer in an enterprise environment.
Built multi agent orchestrations using (Lang-graph, Crew AI, Claude SDK, Open AI SDK, etc).
Have a GitHub repo with an agent/plugins you have created.
Additional AI certifications or experience with agentic tooling and frameworks.
Defined or worked with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry / stream-based architectures.
Understand the AI-native paradigm — blending cloud-native with generative model architectures — optimizing for performance, modularity, and efficiency.
Delivered solutions across multiple industries (e.g., finance, healthcare) by tailoring agentic workflows to industry needs.
Driven execution across multiple workstreams, ensuring quality, delivery, and alignment with client outcomes.

Responsibilities

Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and enablement.
Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.
Tailor and deploy agentic applications across verticals — e.g., finance, healthcare, retail — addressing domain-specific processes via intelligent automation.
Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.