Junior Applied AI Engineer (all genders)

Accenture DACH; Kronberg im Taunus; Híbrido; EUR 85 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

AI certifications

Training resources

Hybrid work model

Mentoring and coaching

Exposure to Anthropic/OpenAI/Microsoft

Resumo da oferta

Accenture DACH is seeking an AI Engineer (Software) to design, build, and ship full-stack software that leverages AI-assisted tooling as a core practice. You will work on client programs across industries, integrating agentic AI systems, LLM APIs, and enterprise AI pipelines.

You will join a team driven to deliver production-grade software, contribute to standards, and pursue a clear path toward advanced AI and forward-deployed roles within a global ecosystem. Hybrid work is offered.

Qualificações

• Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
• Exposure to commercial software engineering in production environments or demonstrated via projects.

Responsabilidades

• Use AI coding assistants daily to improve productivity and output quality.
• Integrate LLM APIs into production applications, manage token limits and latency.
• Apply AI across the full software delivery lifecycle including AI-generated tests and debugging.
• Own the quality of AI-generated outputs and assess production readiness.
• Define and track KPIs for AI-assisted workflows for stakeholders.
• Deliver end-to-end in Agile sprint cycles alongside client teams.
• Contribute to internal AI tooling standards and reusable components.
• Build application layers and interfaces connecting full-stack systems to agentic backends.

Conhecimentos

German language

English language

Backend development

Cloud fundamentals

Docker

CI/CD

SQL/NoSQL databases

LLM API integration

Python/Java/TypeScript

Agile delivery

Formação académica

Bachelor's degree in Computer Science or related field

Ferramentas

Docker

LangChain

LangGraph

REST APIs

Descrição da oferta de emprego

We are building the next generation of AI-native engineering talent engineers who use AI as a core part of how they work, not as an add-on. As an AI Engineer (Software), you will design, build, and ship production-grade software across the full stack, using AI-assisted tooling as standard daily practice alongside your core engineering skills.

You will work on real client programs across industries, building production-grade software that connects to and supports agentic AI systems — understanding how your full-stack work integrates with agent architecture, LLM APIs, and enterprise AI pipelines. This is not a stepping-stone role: it is a core engineering function in the most in-demand part of the market, with a direct pathway to the Forward Deployed Engineer program for those who develop agentic depth.

We offer what no single product company can: breadth across every industry, every enterprise technology stack, and every level of organizational complexity — combined with vendor fellowship access inside Anthropic, OpenAI, Microsoft, and Google engineering teams, structured AI certification pathways, and a clear development track toward agentic and forward-deployed engineering.

Key Responsibilities

• Use AI coding assistants daily as a standard part of delivery, actively, frequently, and with demonstrable impact on productivity and output quality;
• Integrate LLM APIs into applications in production: 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: AI-generated tests, AI-assisted debugging, AI-accelerated code review, and prompt engineering for development tasks;
• Own the quality of AI-generated outputs in your delivery scope, exercise engineering judgment about reliability, limitations, and failure modes; know when AI output is production-ready and when it is not;
• Define and track KPIs to evaluate the effectiveness and ROI of AI-assisted workflows; present AI productivity and quality metrics to project stakeholders;
• Own delivery end-to-end — from design through to 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 the application layers, APIs, and interfaces that connect full-stack systems to agentic backends — understanding data flows, context handoffs, and integration points between your code and AI pipelines.
• Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or a related field;
• Exposure to commercial software engineering experience in production environments (or equivalent demonstrated through academic projects, internships, or shipped personal projects);
• 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 how AI was used to solve real problems, iterate on outputs, and improve delivery; including direct experience calling LLM APIs in production code with an understanding of 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; understanding of AI limitations and responsible use;
• Familiarity with agentic system concepts — awareness of orchestration frameworks (LangChain, LangGraph, or equivalent), RAG pipelines, and how full-stack applications connect to agent-based architecture; production experience preferred, conceptual understanding required.
• Very good German and English language skills, as well as a willingness to travel occasionally for business purposes.

What We Offer

• Access to structured AI certifications, continuous learning opportunities, and more than 30,000 training resources to accelerate your career development;
• The opportunity to work with leading AI technologies and gain exposure to teams across Anthropic, OpenAI, Microsoft, and Google ecosystems;
• Flexible working models, including hybrid working options that support work-life balance;
• Mentoring, coaching, and clear career pathways toward advanced AI and Forward Deployed Engineering roles;
• Exciting projects across industries, technologies, and enterprise environments, providing exceptional breadth of experience.