Full Stack AI Engineer (m/f/d) at Integrity Next GmbH

Munich, Bavaria, Germany -

Full Time

Start Date

Immediate

Expiry Date

21 Sep, 26

Salary

0.0

Posted On

23 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, LangChain, LangGraph, Amazon Bedrock, AWS, React, RAG, Prompt Engineering, API Design, Unstructured Data Processing, Agentic AI, OpenSearch, DynamoDB, S3, Playwright, Puppeteer

Industry

Information Technology & Services

Description

Join us! At IntegrityNext, we are building a shared AI and data platform on AWS on top of our supply chain and product compliance platform. This platform will power semantic data access, BI, APIs, and agentic product experiences across our product landscape. As AI Application Engineer (m/f/d), you will build and ship AI-powered product capabilities end-to-end. You will work hands-on across Python-based AI services, agent workflows, web and document retrieval pipelines, unstructured data processing, APIs, integrations, and lightweight React prototypes where needed. Our AI application layer is built around LangChain, LangGraph, Deep Agents, and Amazon Bedrock AgentCore. The focus is on product delivery rather than research, covering both structured-data-driven AI experiences and unstructured-data processing for retrieval, agent workflows, and future AI-native product capabilities. We work according to “You build it, you run it”, own capabilities from design to production operations, follow spec-driven development, and actively use AI-assisted engineering tools such as Claude Code, Cursor, and similar tools. What can you expect? Build agentic AI product capabilities Build AI-powered product features using retrieval mechanisms, workflows, tools, and multi-step agent patterns Turn product and business needs into reusable, reliable AI capabilities for internal and customer-facing use cases Implement AI capabilities in Python using LangChain, LangGraph, Deep Agents, and Bedrock AgentCore Design and build AI APIs with clean service boundaries for integration into Java-based product systems Work with structured, unstructured, web, and document data Build and maintain retrieval and unstructured-data processing pipelines for documents, web content, and other sources used in agent workflows Work with content and PDF extraction, link following, candidate ranking and selection, deduplication, and source or provenance tracking Collaborate with platform and semantic teams to ground AI features in reliable, well-structured data Support AI experiences based on structured business data, semantic layers, and analytics-driven use cases Improve AI quality, reliability, and production readiness Drive prompt engineering and context engineering to improve quality, reliability, and usability Implement evals, regression checks, prompt-injection tests, scenario-based validation, and quality controls Help define evaluation harnesses, testing approaches, and validation methods for agentic and retrieval systems Support AI observability, tracing, quality monitoring, maintainability, and production operations Contribute across product and engineering layers Contribute to lightweight frontend prototypes and conversational or workflow-driven UI flows in React where needed Work closely with semantic, data platform, architecture, product, and engineering teams Help establish practical spec-driven and AI-assisted engineering workflows that improve quality, speed, and maintainability What should you bring along? Experience & Domain Focus Strong practical experience with Python and proven experience building AI-powered product features in production or near-production environments Experience with LLM application development, including agentic RAG, tool use, workflow orchestration, prompt engineering, and context design Strong knowledge of agentic AI concepts such as agent workflows, planning patterns, tool usage, multi-step reasoning architectures, and agent harnesses Experience building multi-step agents or pipelines that retrieve, read, and reason over information from web and document sources with a focus on grounding, attribution, and reliability Experience building or maintaining unstructured-data pipelines for AI applications, including document and web-page processing, text extraction, retrieval, and AI-oriented data preparation Experience designing backend APIs and integrating AI capabilities into larger product landscapes through clear service boundaries Technical / Methodological Skills Hands-on experience with LangChain and/or LangGraph Familiarity with Deep Agents or similar multi-step or planning-oriented agent harnesses is a strong plus Knowledge of Amazon Bedrock AgentCore and strong overall AWS knowledge, including OpenSearch, S3, and DynamoDB Experience with web search APIs such as SERP API, Linkup, or Tavily, and crawling or extraction frameworks such as Firecrawl or Crawl4AI Experience with headless or JS-rendering fetching using tools such as Playwright or Puppeteer Comfortable with content and PDF extraction, link following, candidate ranking and selection, deduplication, and source or provenance tracking across varied, multilingual, and often unreliable web sources Experience with MCPs, A2A, AgentCore Gateway, Agent Skills, Agent plugins, and testing these components Experience with evaluation harnesses, regression testing, prompt-injection testing, and quality controls for AI and retrieval systems Experience with observability, tracing, or monitoring for AI or backend systems Ability to contribute to lightweight frontend or prototype work in React when needed Ways of Working & Mindset Strong product delivery mindset with a focus on building and shipping AI-powered capabilities end-to-end Comfortable owning AI-powered features in production, not just prototyping them Strong quality mindset and the ability to improve AI systems through testing, evaluation, iteration, and harness-based validation Comfortable working with structured specifications, clear interfaces, spec-driven development, and AI-assisted engineering workflows Deep specialization in AI engineering combined with the willingness to contribute across adjacent layers when needed Practical, hands-on approach to solving complex product and platform challenges Communication & Collaboration Comfortable collaborating closely with semantic, data platform, architecture, product, and engineering teams Able to work across backend implementation, AI application development, APIs, and lightweight frontend prototyping Strong ability to translate product and business needs into reliable technical capabilities Clear communication style and willingness to share knowledge across teams Fluent English skills for working effectively in an English-speaking environment Nice to have Experience with large-scale or polite crawling, deduplication, and source or provenance tracking Experience with entity resolution and attribution across heterogeneous web sources Experience with multilingual document and web-content processing and retrieval Experience designing agentic architectures, evaluation harnesses, and quality frameworks for AI systems Experience with AI observability and tracing tools Experience with React and frontend prototyping for conversational or workflow-driven experiences Experience working with structured business data, semantic layers, or analytics-driven AI use cases Experience with advanced document pipelines, retrieval systems, and unstructured-data-based AI features Experience in multi-team SaaS environments What do we offer? Purpose & Impact A role with real meaning that is both enjoyable and impactful The opportunity to make a sustainable contribution through your work Attractive compensation as part of a growing company Attractive Benefits 30 days of paid vacation EGYM Wellpass membership to support your work-life balance Flexible working models to better balance work and personal life Modern Work Environment & Flexibility Inspiring office spaces in the heart of Munich Flexible remote work from home or anywhere within Germany Great Team A professional, welcoming, and highly motivated team Collaboration at eye level with an open feedback culture An environment where people support each other and grow together Flat Hierarchies & Ownership Short decision-making paths and real opportunities to shape things Freedom to contribute and implement your own ideas A high level of ownership and responsibility Application process About us IntegrityNext, a global leader in supply chain sustainability software, stands at the forefront of corporate sustainability and compliance. Since 2016, businesses have trusted IntegrityNext to simplify ESG compliance, reduce risks, and address critical challenges like due diligence, decarbonization, and sustainability reporting. With over 500 customers and 2 million suppliers across 190 countries, IntegrityNext is transforming supply chains into engines of transparency and sustainable growth. For more information, visit www.integritynext.com. We are an equal opportunity employer and do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We welcome applicants from all backgrounds and strive to create an environment where everyone feels respected and heard. Join us in our mission to build a more equitable and inclusive world.

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Responsibilities

Build and ship end-to-end AI-powered product capabilities, focusing on agentic workflows and retrieval pipelines. Collaborate with cross-functional teams to integrate AI APIs into Java-based systems and ensure production readiness through rigorous evaluation.