AI Native Software Engineer - Products

We Are Accenture is building a new portfolio of agentic software products in the industries we have spent decades helping to transform. We begin with advantages most product companies do not have: deep industry expertise, trusted relationships with many of the world’s largest organizations, and direct access to the complex workflows and problems that matter most to them. That allows us to build closely with customers while creating repeatable products that can be taken broadly to market. We are forming small, highly capable product teams to do this. These teams bring product management, design, and engineering together with the autonomy to move quickly, make decisions, and own outcomes from the earliest prototype through production and scale. This is a software engineering role within a permanent product team. It is not a consulting delivery, data engineering, product management, or forward-deployed engineering role. You Are You are an exceptional AI-native software engineer who has built and shipped production products across the full stack. You combine strong engineering fundamentals with product judgment, systems thinking, and a high bar for quality. You are comfortable beginning with an ambiguous customer or business problem, shaping the technical approach, and turning it into software that real users rely on. AI is central to both what you build and how you build. You use coding agents and other AI development tools as a core part of your daily workflow. You know how to decompose work, provide the right context and constraints, establish tests and evaluations, and review generated output with rigor. You use AI to increase your leverage while retaining full accountability for the architecture, security, reliability, and quality of the product. You are energized by zero-to-one work, small teams, high autonomy, and the opportunity to help define how a new product engineering organization should operate. What You Will Do Build and ship across the full stack. Own meaningful product capabilities end to end, including application architecture, data models, backend services, APIs, integrations, AI systems, and user experiences. Work directly with product managers and designers to turn customer problems into simple, high-quality products. Move comfortably between prototyping and production engineering, making thoughtful decisions about when to optimize for speed and when to invest for scale, security, and reliability. Build AI-native products. Design and implement agentic systems, including model interactions, tool use, retrieval, orchestration, state management, evaluations, observability, and guardrails. Build products that perform reliably against complex, real-world industry workflows rather than only in controlled demonstrations. Evaluate model and system behavior rigorously, understand failure modes, and improve the product through evidence. Work in an AI-native engineering model. Use coding agents and AI development tools extensively throughout the engineering lifecycle. Create the context, specifications, tests, development environments, CI pipelines, and evaluation systems that allow agents to produce high-quality work safely and efficiently. Direct multiple streams of agent-assisted work where appropriate, review outputs critically, and remain accountable for everything that reaches production. Set technical direction. Translate ambiguous product opportunities into clear technical approaches and executable plans. Make sound architecture decisions for new product areas and carry those decisions from prototype through production. Balance speed, simplicity, extensibility, security, cost, and operational reliability. Identify where the team should build, buy, integrate, or deliberately defer. Own product and production outcomes. Stay close to users and customers and understand the workflows your software is changing. Use customer feedback, product data, evaluations, and operational signals to improve the product continuously. Own reliability, observability, security, performance, and maintainability in production. Treat successful adoption and customer outcomes as engineering concerns. Raise the engineering bar. Provide rigorous technical review on the work that matters most. Help other engineers improve their judgment, execution, and use of AI-native development practices. Contribute to the shared architecture, tools, standards, and operating practices of the broader product engineering organization. Help define how small, AI-native product teams should work as the company grows. What You Bring: Minimum of 5 years eight years of experience building and shipping production software. Minimum of 8 years experience building across the full stack, including frontend and backend systems. Minimum of 5 years ​ software engineering fundamentals, including system design, data modeling, APIs, testing, cloud-native development, security, observability, and production operations. Minimum 2 years of substantive, hands-on AI-native engineering experience as part of your day-to-day work. This may include building with LLM APIs, coding agents, agent frameworks, tool integrations, retrieval systems, evaluation frameworks, or production guardrails. Minimum 1 year of experience building reliable AI or agentic systems that operate beyond a prototype or demonstration environment including a track record of taking products, systems, or major capabilities from zero to one and owning them through production. Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience). Required Professional Skills: Demonstrated ability to use AI development tools to materially increase engineering leverage without lowering the quality bar Excellent judgment under ambiguity and the ability to make progress without complete information. Strong product instincts and the ability to recognize what makes a product useful, intuitive, and well crafted. The ability to communicate technical decisions clearly and work closely with product managers, designers, customers, and domain experts. The ability to communicate technical decisions clearly and work closely with product managers, designers, customers, and domain experts. A genuine interest in frontier AI and a consistent habit of testing new models, tools, and engineering approaches in practice. Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below. We anticipate this job posting will be posted until 11/20/2026. 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 About Accenture Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. 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