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Accenture

Advises businesses and runs their technology

AI Native Software Engineer - Data & AI

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • A bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related field is required.
  • Software engineering experience in production environments, or equivalent demonstrated through academic projects, internships, or shipped personal projects, is required.
  • Proficiency in at least one primary backend language: Python, Java, or TypeScript.
  • Demonstrated hands-on experience using AI tools actively in day-to-day engineering work, with practical examples of solving real problems, iterating on outputs, and improving delivery, including direct experience calling LLM APIs in production code and understanding token management, latency, and cost tradeoffs.
  • Basic understanding of web technologies including JavaScript, HTML, and CSS.
  • Familiarity with cloud fundamentals (AWS, Azure, or GCP), containers (Docker), and CI/CD pipelines.
  • Understanding of Agile delivery fundamentals.
  • Experience with databases, SQL or NoSQL.
  • Ability to validate, evaluate, and improve AI-generated outputs, with an understanding of AI limitations and responsible use.
  • Conceptual understanding of agentic system concepts, including orchestration frameworks such as LangChain, LangGraph, or equivalent, RAG pipelines, and how full-stack applications connect to agent-based architecture.
  • Very good German and English skills.

Responsibilities

  • Use AI coding assistants daily as a standard part of delivery, frequently and with demonstrable impact on productivity and output quality.
  • Integrate LLM APIs into production applications by calling AI provider APIs in live code, managing token limits and latency, and building initial abstraction layers.
  • Apply AI across the full software delivery lifecycle through AI-generated tests, AI-assisted debugging, AI-accelerated code review, and prompt engineering for development tasks.
  • Own the quality of AI-generated outputs in the delivery scope and exercise engineering judgment about reliability, limitations, and failure modes, including deciding when AI output is production-ready.
  • Define and track KPIs to evaluate the effectiveness and ROI of AI-assisted workflows, and present AI productivity and quality metrics to project stakeholders.
  • Own delivery end-to-end, from design through production support, in Agile sprint cycles alongside client engineering teams.
  • Contribute to shared knowledge bases, reusable components, and internal AI tooling standards that benefit the wider team.
  • Build and integrate application layers, APIs, and interfaces connecting full-stack systems to agentic backends, including understanding data flows, context handoffs, and integration points between the code and AI pipelines.

Desired Qualifications

  • Production experience with agentic system concepts, orchestration frameworks, RAG pipelines, or integrations with agent-based architecture.

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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