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Accenture

Advises businesses and runs their technology

AI Native Software Engineer - Products

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • A bachelor's degree or equivalent (minimum 12 years) of work experience is required. An associate's degree is acceptable with a minimum of 6 years of work experience.
  • At least 3 years of experience building and shipping production software.
  • At least 3 years of experience building across the full stack, including frontend and backend systems.
  • At least 3 years of software engineering fundamentals, including system design, data modeling, APIs, testing, cloud-native development, security, observability, and production operations.
  • At least 1 year of substantive, hands-on AI-native engineering experience as part of day-to-day work, such as building with large language model APIs, coding agents, agent frameworks, tool integrations, retrieval systems, evaluation frameworks, or production guardrails.
  • At least 1 year of experience building reliable AI or agentic systems beyond prototype or demonstration environments, including a track record of taking products, systems, or major capabilities from zero to one and owning them through production.
  • Demonstrated ability to use AI development tools to materially increase engineering leverage without lowering the quality bar.
  • Sound 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.
  • Ability to communicate technical decisions clearly and work closely with product managers, designers, customers, and domain experts.
  • Genuine interest in frontier AI and a consistent habit of testing new models, tools, and engineering approaches in practice.

Responsibilities

  • Build and ship full-stack 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 between prototyping and production engineering, deciding when to optimize for speed and when to invest in scale, security, and reliability.
  • 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; rigorously evaluate model and system behavior, understand failure modes, and improve products using evidence.
  • Use coding agents and AI development tools throughout the engineering lifecycle; create the context, specifications, tests, development environments, continuous integration pipelines, and evaluation systems agents need to produce high-quality work safely and efficiently.
  • Direct multiple streams of agent-assisted work where appropriate, critically review outputs, and remain accountable for everything that reaches production.
  • Translate ambiguous product opportunities into technical approaches and executable plans; make architecture decisions and carry them from prototype through production.
  • Balance speed, simplicity, extensibility, security, cost, and operational reliability, and identify where to build, buy, integrate, or defer.
  • Stay close to users and customers and understand the workflows the software changes; use customer feedback, product data, evaluations, and operational signals to improve the product continuously.
  • Own reliability, observability, security, performance, and maintainability in production, treating successful adoption and customer outcomes as engineering concerns.
  • Provide rigorous technical review on important work and help other engineers improve their judgment, execution, and use of AI-native development practices.
  • Contribute to shared architecture, tools, standards, and operating practices of the broader product engineering organization, and help define how small AI-native product teams should work as the company grows.
  • Spend time onsite with clients and partners as required to deliver services.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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