Abrar Admin

Integrity Next

<div><h4 class="jobSectionHeader"><b>Join us!</b></h4><p>
At IntegrityNext, we are building a shared AI and data platform on AWS on top of our supply chain and product compliance platform. The platform powers semantic data access, BI, APIs, and agentic product experiences.<br>
Our PostgreSQL operational databases are ingested into Snowflake through a near-real-time pipeline built on Snowflake Openflow. On top of Snowflake, we transform and model data with dbt, expose business meaning through Snowflake semantic views, use Snowflake Cortex AI for AI capabilities, and surface curated data through Amazon QuickSight, Apache Superset, APIs, and AI consumption layers.<br>
<br>
As <b>Fullstack Engineer (Semantic / Analytics) (m/f/d)</b>, you will own the business meaning of data and make it reusable across analytics, BI, APIs, semantic access, and AI-powered experiences. You will work across semantic modeling, KPI logic, reusable data models, business-facing data exposure, and collaborate closely with platform, AI, solution, and business teams.<br>
<br>
The platform will continue to evolve toward broader support for unstructured data and lakehouse-style capabilities. We work spec-driven, use AI-assisted engineering tools such as Claude Code and Cursor, follow &ldquo;You build it, you run it&rdquo;, and expect strong specialization combined with fullstack ownership.</p><h4 class="jobSectionHeader"><b><br>
What can you expect?</b></h4><p><b>
Build the semantic foundation for data products</b></p><ul><li>
Build and evolve the semantic layer in dbt and Snowflake semantic views, including business entities, metrics, dimensions, and reusable data models</li><li>
Define KPIs, business logic, canonical data definitions, and semantic consistency standards together with business and product stakeholders</li><li>
Help shape how semantic data products are exposed consistently across internal and external platform capabilities</li><li>
Ensure business entities, KPIs, and metrics are clearly and consistently defined across the platform</li></ul><b>
Make curated data usable across BI, APIs, and AI</b><ul><li>
Expose curated data for BI tools such as Amazon QuickSight and Apache Superset, APIs, downstream product use cases, and AI consumption including Snowflake Cortex AI</li><li>
Support AI use cases through feature shaping, context structuring, semantic enrichment, and business-grounded data preparation</li><li>
Collaborate with the AI Engineer to ensure agentic experiences are grounded in meaningful, well-structured business data</li><li>
Help ensure BI, APIs, and AI use cases rely on the same trusted semantic foundations in Snowflake</li></ul><b>
Work with reliable, fresh, and governed data</b><ul><li>
Work with near-real-time data ingested from PostgreSQL into Snowflake via Snowflake Openflow</li><li>
Ensure semantic models reflect fresh, reliable data from operational systems</li><li>
Align with solution teams on data contracts, source semantics, and integration expectations</li><li>
Help define validation rules, data trust practices, lineage support, and consistency controls</li></ul><b>
Collaborate across platform, product, and engineering</b><ul><li>
Work closely with the Data &amp; Platform Architect and Data &amp; Platform Engineer to build semantic models on reliable, scalable Snowflake foundations</li><li>
Collaborate with platform, AI, solution, product, and business-facing teams</li><li>
Help the company build a reusable semantic layer that scales with future platform growth</li><li>
Apply spec-driven development, AI-assisted engineering workflows, and end-to-end production ownership</li></ul><p></p><h4 class="jobSectionHeader"><b>
What should you bring along?</b></h4><p><b>
Experience &amp; Domain Focus</b></p><ul><li>
Very strong hands-on SQL skills and broad, deep database knowledge, including data modeling</li><li>
Strong hands-on experience with Snowflake, including Snowflake semantic views</li><li>
Hands-on experience with dbt at scale for transformations and analytics engineering best practices</li><li>
Experience with PostgreSQL as a source for structured business data</li><li>
Experience building semantic layers, reusable metrics, canonical data models, analytics engineering assets, KPIs, business logic, and data definitions with stakeholders</li><li>
Experience exposing data for BI, APIs, downstream product use cases, and AI or analytics consumption</li><li>
Experience defining or supporting data contracts, validation rules, semantic consistency standards, data quality, lineage, and trust practices</li></ul><b>
Technical / Methodological Skills</b><ul><li>
Experience with near-real-time or CDC ingestion, ideally Snowflake Openflow or comparable tools such as Fivetran, Debezium, or Kafka</li><li>
Strong Python skills</li><li>
Experience building APIs and services such as REST or GraphQL</li><li>
Experience exposing data and tools through interfaces such as MCP servers</li><li>
Solid AWS stack know-how</li><li>
Experience with BI tools such as Amazon QuickSight, Apache Superset, Looker, Tableau, Power BI, or similar platforms</li><li>
Strong understanding of how data should be structured for AI, analytics, semantic access, and product consumption</li><li>
Comfortable with structured, spec-driven delivery and AI-assisted development workflows</li></ul><b>
Ways of Working &amp; Mindset</b><ul><li>
Fullstack ownership mindset with the ability to own capabilities from design and implementation to production operations</li><li>
Strong specialization in semantic and analytics engineering combined with the willingness to contribute across adjacent layers</li><li>
Ability to translate business meaning into reliable, reusable, and scalable data products</li><li>
Strong quality mindset around semantic consistency, validation, data trust, and long-term maintainability</li><li>
Comfortable working in an evolving platform environment that may expand toward unstructured data and lakehouse-style capabilities</li></ul><b>
Communication &amp; Collaboration</b><ul><li>
Ability to work closely with platform, AI, solution, product, and business-facing teams</li><li>
Strong collaboration skills for aligning on contracts, source semantics, KPI logic, and integration expectations</li><li>
Clear communication style when translating technical data models into business meaning</li><li>
Comfortable collaborating with Data &amp; Platform Architecture, Data Engineering, AI Engineering, and solution teams</li><li>
Fluent English skills for working effectively in an English-speaking environment</li></ul><b>
Nice to have</b><ul><li>
Some AI agent engineering experience, ideally with Amazon Bedrock AgentCore or frameworks such as LangChain, LangGraph, or Deep Agents</li><li>
Some data science experience, such as statistics, feature engineering, experimentation, or machine learning</li><li>
Experience with Snowflake Cortex AI</li><li>
Experience supporting AI use cases through feature engineering, context shaping, or semantic enrichment</li><li>
Experience with data quality, lineage, and validation practices</li><li>
Experience in multi-team SaaS environments</li><li>
Experience with unstructured data enrichment or hybrid structured and unstructured semantic models</li><li>
General understanding of Java and/or frontend React</li></ul><p></p><h4 class="jobSectionHeader"><b>
What do we offer?</b></h4><p></p><h3 class="jobSectionHeader"><b>
Purpose &amp; Impact</b></h3><ul><li><div>
A role with real meaning that is both enjoyable and impactful</div></li><li><div>
The opportunity to make a sustainable contribution through your work</div></li><li><div>
Attractive compensation as part of a growing company</div></li></ul><h3 class="jobSectionHeader"><b>
Attractive Benefits</b></h3><ul><li><div>
30 days of paid vacation</div></li><li><div>
EGYM Wellpass membership to support your work-life balance</div></li><li><div>
Flexible working models to better balance work and personal life</div></li></ul><h3 class="jobSectionHeader"><b>
Modern Work Environment &amp; Flexibility</b></h3><ul><li><div>
Inspiring office spaces in the heart of Munich</div></li><li><div>
Flexible remote work from home or anywhere within Germany</div></li></ul><h3 class="jobSectionHeader"><b>
Great Team</b></h3><ul><li><div>
A professional, welcoming, and highly motivated team</div></li><li><div>
Collaboration at eye level with an open feedback culture</div></li><li><div>
An environment where people support each other and grow together</div></li></ul><h3 class="jobSectionHeader"><b>
Flat Hierarchies &amp; Ownership</b></h3><ul><li><div>
Short decision-making paths and real opportunities to shape things</div></li><li><div>
Freedom to contribute and implement your own ideas</div></li><li><div>
A high level of ownership and responsibility</div></li></ul><p></p><h4 class="jobSectionHeader"><b><br>
Application process</b></h4><p><i>
Please apply exclusively via our online application portal. This ensures a smooth and fair process for all candidates. Applications submitted by email or LinkedIn will not be considered. Thank you for your understanding.</i></p><h4 class="jobSectionHeader"><b>
About us</b></h4><p>
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.<br>
<br>
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.</p></div>

Fullstack Engineer (Semantic / Analytics) (m/f/d)

<div><div><div><div><div>Mobile Work</div><div>
Full-time</div><div>
Permanent employee</div></div></div></div><p>
</p><div><div><h2 class="jobSectionHeader"><b>
Join us!</b></h2><div>
At IntegrityNext, we are building a shared AI and data platform on AWS on top of our supply chain and product compliance platform. The platform powers semantic data access, BI, APIs, and agentic product experiences.<br>
Our PostgreSQL operational databases are ingested into Snowflake through a near-real-time pipeline built on Snowflake Openflow. On top of Snowflake, we transform and model data with dbt, expose business meaning through Snowflake semantic views, use Snowflake Cortex AI for AI capabilities, and surface curated data through Amazon QuickSight, Apache Superset, APIs, and AI consumption layers.<br>
<br>
As <b>Fullstack Engineer (Semantic / Analytics) (m/f/d)</b>, you will own the business meaning of data and make it reusable across analytics, BI, APIs, semantic access, and AI-powered experiences. You will work across semantic modeling, KPI logic, reusable data models, business-facing data exposure, and collaborate closely with platform, AI, solution, and business teams.<br>
<br>
The platform will continue to evolve toward broader support for unstructured data and lakehouse-style capabilities. We work spec-driven, use AI-assisted engineering tools such as Claude Code and Cursor, follow &ldquo;You build it, you run it&rdquo;, and expect strong specialization combined with fullstack ownership.</div></div><div><h2 class="jobSectionHeader"><b>
What can you expect?</b></h2><div><b>
Build the semantic foundation for data products</b><ul><li>
Build and evolve the semantic layer in dbt and Snowflake semantic views, including business entities, metrics, dimensions, and reusable data models</li><li>
Define KPIs, business logic, canonical data definitions, and semantic consistency standards together with business and product stakeholders</li><li>
Help shape how semantic data products are exposed consistently across internal and external platform capabilities</li><li>
Ensure business entities, KPIs, and metrics are clearly and consistently defined across the platform</li></ul><b>
Make curated data usable across BI, APIs, and AI</b><ul><li>
Expose curated data for BI tools such as Amazon QuickSight and Apache Superset, APIs, downstream product use cases, and AI consumption including Snowflake Cortex AI</li><li>
Support AI use cases through feature shaping, context structuring, semantic enrichment, and business-grounded data preparation</li><li>
Collaborate with the AI Engineer to ensure agentic experiences are grounded in meaningful, well-structured business data</li><li>
Help ensure BI, APIs, and AI use cases rely on the same trusted semantic foundations in Snowflake</li></ul><b>
Work with reliable, fresh, and governed data</b><ul><li>
Work with near-real-time data ingested from PostgreSQL into Snowflake via Snowflake Openflow</li><li>
Ensure semantic models reflect fresh, reliable data from operational systems</li><li>
Align with solution teams on data contracts, source semantics, and integration expectations</li><li>
Help define validation rules, data trust practices, lineage support, and consistency controls</li></ul><b>
Collaborate across platform, product, and engineering</b><ul><li>
Work closely with the Data &amp; Platform Architect and Data &amp; Platform Engineer to build semantic models on reliable, scalable Snowflake foundations</li><li>
Collaborate with platform, AI, solution, product, and business-facing teams</li><li>
Help the company build a reusable semantic layer that scales with future platform growth</li><li>
Apply spec-driven development, AI-assisted engineering workflows, and end-to-end production ownership</li></ul></div></div><div><h2 class="jobSectionHeader"><b>
What should you bring along?</b></h2><div><b>
Experience &amp; Domain Focus</b><ul><li>
Very strong hands-on SQL skills and broad, deep database knowledge, including data modeling</li><li>
Strong hands-on experience with Snowflake, including Snowflake semantic views</li><li>
Hands-on experience with dbt at scale for transformations and analytics engineering best practices</li><li>
Experience with PostgreSQL as a source for structured business data</li><li>
Experience building semantic layers, reusable metrics, canonical data models, analytics engineering assets, KPIs, business logic, and data definitions with stakeholders</li><li>
Experience exposing data for BI, APIs, downstream product use cases, and AI or analytics consumption</li><li>
Experience defining or supporting data contracts, validation rules, semantic consistency standards, data quality, lineage, and trust practices</li></ul><b>
Technical / Methodological Skills</b><ul><li>
Experience with near-real-time or CDC ingestion, ideally Snowflake Openflow or comparable tools such as Fivetran, Debezium, or Kafka</li><li>
Strong Python skills</li><li>
Experience building APIs and services such as REST or GraphQL</li><li>
Experience exposing data and tools through interfaces such as MCP servers</li><li>
Solid AWS stack know-how</li><li>
Experience with BI tools such as Amazon QuickSight, Apache Superset, Looker, Tableau, Power BI, or similar platforms</li><li>
Strong understanding of how data should be structured for AI, analytics, semantic access, and product consumption</li><li>
Comfortable with structured, spec-driven delivery and AI-assisted development workflows</li></ul><b>
Ways of Working &amp; Mindset</b><ul><li>
Fullstack ownership mindset with the ability to own capabilities from design and implementation to production operations</li><li>
Strong specialization in semantic and analytics engineering combined with the willingness to contribute across adjacent layers</li><li>
Ability to translate business meaning into reliable, reusable, and scalable data products</li><li>
Strong quality mindset around semantic consistency, validation, data trust, and long-term maintainability</li><li>
Comfortable working in an evolving platform environment that may expand toward unstructured data and lakehouse-style capabilities</li></ul><b>
Communication &amp; Collaboration</b><ul><li>
Ability to work closely with platform, AI, solution, product, and business-facing teams</li><li>
Strong collaboration skills for aligning on contracts, source semantics, KPI logic, and integration expectations</li><li>
Clear communication style when translating technical data models into business meaning</li><li>
Comfortable collaborating with Data &amp; Platform Architecture, Data Engineering, AI Engineering, and solution teams</li><li>
Fluent English skills for working effectively in an English-speaking environment</li></ul><b>
Nice to have</b><ul><li>
Some AI agent engineering experience, ideally with Amazon Bedrock AgentCore or frameworks such as LangChain, LangGraph, or Deep Agents</li><li>
Some data science experience, such as statistics, feature engineering, experimentation, or machine learning</li><li>
Experience with Snowflake Cortex AI</li><li>
Experience supporting AI use cases through feature engineering, context shaping, or semantic enrichment</li><li>
Experience with data quality, lineage, and validation practices</li><li>
Experience in multi-team SaaS environments</li><li>
Experience with unstructured data enrichment or hybrid structured and unstructured semantic models</li><li>
General understanding of Java and/or frontend React</li></ul></div></div><div><h2 class="jobSectionHeader"><b>
What do we offer?</b></h2><div><h3 class="jobSectionHeader"><b>
Purpose &amp; Impact</b></h3><ul><li><div>
A role with real meaning that is both enjoyable and impactful</div></li><li><div>
The opportunity to make a sustainable contribution through your work</div></li><li><div>
Attractive compensation as part of a growing company</div></li></ul><h3 class="jobSectionHeader"><b>
Attractive Benefits</b></h3><ul><li><div>
30 days of paid vacation</div></li><li><div>
EGYM Wellpass membership to support your work-life balance</div></li><li><div>
Flexible working models to better balance work and personal life</div></li></ul><h3 class="jobSectionHeader"><b>
Modern Work Environment &amp; Flexibility</b></h3><ul><li><div>
Inspiring office spaces in the heart of Munich</div></li><li><div>
Flexible remote work from home or anywhere within Germany</div></li></ul><h3 class="jobSectionHeader"><b>
Great Team</b></h3><ul><li><div>
A professional, welcoming, and highly motivated team</div></li><li><div>
Collaboration at eye level with an open feedback culture</div></li><li><div>
An environment where people support each other and grow together</div></li></ul><h3 class="jobSectionHeader"><b>
Flat Hierarchies &amp; Ownership</b></h3><ul><li><div>
Short decision-making paths and real opportunities to shape things</div></li><li><div>
Freedom to contribute and implement your own ideas</div></li><li><div>
A high level of ownership and responsibility</div></li></ul></div></div><div><h2 class="jobSectionHeader"><b>
Application process</b></h2><div><i>
Please apply exclusively via our online application portal. This ensures a smooth and fair process for all candidates. Applications submitted by email or LinkedIn will not be considered. Thank you for your understanding.</i></div></div></div><p></p><div><h2 class="jobSectionHeader"><b>
About us</b></h2><div>
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.<br>
<br>
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.</div></div></div><p></p>

<div><div><div><div><div>Mobile Work</div><div>
Full-time</div><div>
Permanent employee</div></div></div></div><p>
</p><div><div><h2 class="jobSectionHeader"><b>
Join us!</b></h2><div>
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.<br>
As <b>AI Application Engineer (m/f/d)</b>, 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.<br>
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.<br>
We work according to &ldquo;You build it, you run it&rdquo;, 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.</div></div><div><h2 class="jobSectionHeader"><b>
What can you expect?</b></h2><div><b>
Build agentic AI product capabilities</b><ul><li>
Build AI-powered product features using retrieval mechanisms, workflows, tools, and multi-step agent patterns</li><li>
Turn product and business needs into reusable, reliable AI capabilities for internal and customer-facing use cases</li><li>
Implement AI capabilities in Python using LangChain, LangGraph, Deep Agents, and Bedrock AgentCore</li><li>
Design and build AI APIs with clean service boundaries for integration into Java-based product systems</li></ul><b>
Work with structured, unstructured, web, and document data</b><ul><li>
Build and maintain retrieval and unstructured-data processing pipelines for documents, web content, and other sources used in agent workflows</li><li>
Work with content and PDF extraction, link following, candidate ranking and selection, deduplication, and source or provenance tracking</li><li>
Collaborate with platform and semantic teams to ground AI features in reliable, well-structured data</li><li>
Support AI experiences based on structured business data, semantic layers, and analytics-driven use cases</li></ul><b>
Improve AI quality, reliability, and production readiness</b><ul><li>
Drive prompt engineering and context engineering to improve quality, reliability, and usability</li><li>
Implement evals, regression checks, prompt-injection tests, scenario-based validation, and quality controls</li><li>
Help define evaluation harnesses, testing approaches, and validation methods for agentic and retrieval systems</li><li>
Support AI observability, tracing, quality monitoring, maintainability, and production operations</li></ul><b>
Contribute across product and engineering layers</b><ul><li>
Contribute to lightweight frontend prototypes and conversational or workflow-driven UI flows in React where needed</li><li>
Work closely with semantic, data platform, architecture, product, and engineering teams</li><li>
Help establish practical spec-driven and AI-assisted engineering workflows that improve quality, speed, and maintainability</li></ul></div></div><div><h2 class="jobSectionHeader"><b>
What should you bring along?</b></h2><div><b>
Experience &amp; Domain Focus</b><ul><li>
Strong practical experience with Python and proven experience building AI-powered product features in production or near-production environments</li><li>
Experience with LLM application development, including agentic RAG, tool use, workflow orchestration, prompt engineering, and context design</li><li>
Strong knowledge of agentic AI concepts such as agent workflows, planning patterns, tool usage, multi-step reasoning architectures, and agent harnesses</li><li>
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</li><li>
Experience building or maintaining unstructured-data pipelines for AI applications, including document and web-page processing, text extraction, retrieval, and AI-oriented data preparation</li><li>
Experience designing backend APIs and integrating AI capabilities into larger product landscapes through clear service boundaries</li></ul><b>
Technical / Methodological Skills</b><ul><li>
Hands-on experience with LangChain and/or LangGraph</li><li>
Familiarity with Deep Agents or similar multi-step or planning-oriented agent harnesses is a strong plus</li><li>
Knowledge of Amazon Bedrock AgentCore and strong overall AWS knowledge, including OpenSearch, S3, and DynamoDB</li><li>
Experience with web search APIs such as SERP API, Linkup, or Tavily, and crawling or extraction frameworks such as Firecrawl or Crawl4AI</li><li>
Experience with headless or JS-rendering fetching using tools such as Playwright or Puppeteer</li><li>
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</li><li>
Experience with MCPs, A2A, AgentCore Gateway, Agent Skills, Agent plugins, and testing these components</li><li>
Experience with evaluation harnesses, regression testing, prompt-injection testing, and quality controls for AI and retrieval systems</li><li>
Experience with observability, tracing, or monitoring for AI or backend systems</li><li>
Ability to contribute to lightweight frontend or prototype work in React when needed</li></ul><b>
Ways of Working &amp; Mindset</b><ul><li>
Strong product delivery mindset with a focus on building and shipping AI-powered capabilities end-to-end</li><li>
Comfortable owning AI-powered features in production, not just prototyping them</li><li>
Strong quality mindset and the ability to improve AI systems through testing, evaluation, iteration, and harness-based validation</li><li>
Comfortable working with structured specifications, clear interfaces, spec-driven development, and AI-assisted engineering workflows</li><li>
Deep specialization in AI engineering combined with the willingness to contribute across adjacent layers when needed</li><li>
Practical, hands-on approach to solving complex product and platform challenges</li></ul><b>
Communication &amp; Collaboration</b><ul><li>
Comfortable collaborating closely with semantic, data platform, architecture, product, and engineering teams</li><li>
Able to work across backend implementation, AI application development, APIs, and lightweight frontend prototyping</li><li>
Strong ability to translate product and business needs into reliable technical capabilities</li><li>
Clear communication style and willingness to share knowledge across teams</li><li>
Fluent English skills for working effectively in an English-speaking environment</li></ul><b>
Nice to have</b><ul><li>
Experience with large-scale or polite crawling, deduplication, and source or provenance tracking</li><li>
Experience with entity resolution and attribution across heterogeneous web sources</li><li>
Experience with multilingual document and web-content processing and retrieval</li><li>
Experience designing agentic architectures, evaluation harnesses, and quality frameworks for AI systems</li><li>
Experience with AI observability and tracing tools</li><li>
Experience with React and frontend prototyping for conversational or workflow-driven experiences</li><li>
Experience working with structured business data, semantic layers, or analytics-driven AI use cases</li><li>
Experience with advanced document pipelines, retrieval systems, and unstructured-data-based AI features</li><li>
Experience in multi-team SaaS environments</li></ul></div></div><div><h2 class="jobSectionHeader"><b>
What do we offer?</b></h2><div><h3 class="jobSectionHeader"><b>
Purpose &amp; Impact</b></h3><ul><li><div>
A role with real meaning that is both enjoyable and impactful</div></li><li><div>
The opportunity to make a sustainable contribution through your work</div></li><li><div>
Attractive compensation as part of a growing company</div></li></ul><h3 class="jobSectionHeader"><b>
Attractive Benefits</b></h3><ul><li><div>
30 days of paid vacation</div></li><li><div>
EGYM Wellpass membership to support your work-life balance</div></li><li><div>
Flexible working models to better balance work and personal life</div></li></ul><h3 class="jobSectionHeader"><b>
Modern Work Environment &amp; Flexibility</b></h3><ul><li><div>
Inspiring office spaces in the heart of Munich</div></li><li><div>
Flexible remote work from home or anywhere within Germany</div></li></ul><h3 class="jobSectionHeader"><b>
Great Team</b></h3><ul><li><div>
A professional, welcoming, and highly motivated team</div></li><li><div>
Collaboration at eye level with an open feedback culture</div></li><li><div>
An environment where people support each other and grow together</div></li></ul><h3 class="jobSectionHeader"><b>
Flat Hierarchies &amp; Ownership</b></h3><ul><li><div>
Short decision-making paths and real opportunities to shape things</div></li><li><div>
Freedom to contribute and implement your own ideas</div></li><li><div>
A high level of ownership and responsibility</div></li></ul></div></div><div><h2 class="jobSectionHeader"><b>
Application process</b></h2><div><i>
Please apply exclusively via our online application portal. This ensures a smooth and fair process for all candidates. Applications submitted by email or LinkedIn will not be considered. Thank you for your understanding.</i></div></div></div><p></p><div><h2 class="jobSectionHeader"><b>
About us</b></h2><div>
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.<br>
<br>
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.</div></div></div><p></p>

Full Stack AI Engineer (m/f/d)

Join Integrity Next and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Integrity Next

About Company

Fullstack Engineer (Semantic / Analytics) (m/f/d)

Fullstack Engineer (Semantic / Analytics) (m/f/d)

Full Stack AI Engineer (m/f/d)