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Accenture

Advises businesses and runs their technology

AI Native Software Engineer - Digital Core, Americas Market

AI Application Engineering +1Confirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A minimum of 3 years of professional software engineering experience building production software is required.
  • A minimum of 2 years of hands-on experience working across more than one layer of the stack, such as front end and API or services and data, is required.
  • A minimum of 3 years of programming experience in at least one major language such as Java, Python, Go, TypeScript, JavaScript, or C# is required.
  • A minimum of 3 years of hands-on experience with a major cloud platform (AWS, Azure, or GCP), including building and deploying containerized services, is required.
  • A minimum of 3 years of experience working within an automated CI/CD pipeline, including writing automated tests, is required.
  • A minimum of 1 year of hands-on experience building and shipping AI-enabled features or agent workflows, including model integration through APIs, tool calling, structured outputs, retrieval, and context engineering, is required.
  • A minimum of 1 year of experience applying AI coding tools to day-to-day software development, including code generation, test generation, debugging, and documentation, is required.
  • A bachelor's degree in Computer Science, Engineering, or equivalent work experience of at least 12 years is required. With an associate's degree, at least 6 years of work experience is required.

Responsibilities

  • Build and ship production features across front end, APIs, backend services, integration, and data, taking a feature end to end across every layer it touches.
  • Read and debug unfamiliar code, trace a problem across application, data, and infrastructure boundaries, and fix the underlying cause.
  • Develop, containerize, and deploy services on a major cloud platform using Docker, Kubernetes or serverless, and managed cloud services.
  • Apply infrastructure as code (Terraform, Helm, or equivalent), and help keep services healthy, observable, and recoverable in production.
  • Work within automated CI/CD pipelines, write automated tests, resolve pipeline failures, and take changes through to production.
  • Apply secure engineering practices while coding, including identity and access fundamentals, secrets handling, dependency hygiene, and input validation.
  • Design and implement data access for features across relational and non-relational stores, APIs, object storage, and event platforms.
  • Build retrieval and context layers for AI features, including knowledge sources, embeddings, metadata, and context management, while applying data quality, access, and privacy controls.
  • Integrate commercial and open models through APIs and enterprise AI platforms, using tool calling, structured outputs, retrieval, and context engineering in live business workflows.
  • Build agent workflows with tools, memory, and human checkpoints, and write evaluations measuring behavior for accuracy, latency, safety, and cost.
  • Use AI-native development techniques for code generation, test generation, debugging, refactoring, documentation, and code comprehension, and measure their effect on throughput and quality.
  • Give agents context, tools, and boundaries for bounded engineering tasks, and review their output to the standard applied to a colleague's code.
  • Participate in design reviews, code reviews, and production troubleshooting; apply feedback quickly and raise the quality of the work around the team.
  • Document learnings and contribute patterns, reusable components, and tooling to the team and internal AI-native engineering community.
  • Travel as required; the amount varies from 25% to 75% depending on business need and client requirements.

Desired Qualifications

  • A public repository, portfolio, or open-source contribution featuring agents, tools, or plugins built by the candidate.
  • Experience with an agent framework such as LangGraph, Crew AI, the Claude Agent SDK, or the OpenAI SDK.
  • Experience writing evaluations or test harnesses that measure AI behavior.
  • Hands-on experience with infrastructure as code and observability tooling.
  • Relevant cloud or AI certifications.
  • Experience in a client-facing or product-facing role presenting the candidate's own technical work to stakeholders.
  • Experience in a startup, product company, or hyperscaler environment owning a feature from idea through production.

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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