Responsible for the semantic architecture, design, and implementation of enterprise knowledge graphs and ontological models that transform unstructured data into interconnected, machine-readable intelligence.
Responsibilities
Engineer domain-specific ontologies, taxonomies, and controlled vocabularies using modern semantic web standards (OWL, RDF, and SHACL).
Design semantic schemas that enable cross-system interoperability, advanced inference, and robust metadata management.
Collaborate with data scientists, software engineers, and AI architects to integrate semantic frameworks with enterprise graph databases (GraphDB, Neo4j).
Integrate semantic frameworks with modern AI pipelines including Retrieval-Augmented Generation (RAG) and vector search structures.
Establish strict data governance, validation workflows, and data harmonization pipelines.
This role focuses on the hands-on development and delivery of production-grade AI solutions that enable automation, insight generation, and scalable intelligence across enterprise platforms.
Compensation
Minimum Salary: zł182,004 Annual
Responsibilities
Design, build, and deploy production AI and ML solutions
Develop LLM-based applications, including prompt engineering and inference workflows
Build RAG pipelines using structured and unstructured enterprise data
Implement embeddings, semantic search, and vector-based retrieval
Develop and lead the group-wide Data & AI platform strategy for Orca Group, creating the technological foundation for next-generation products with a focus on AI and agent-based functions.
Locations (2)
München, Bavaria, Germany
Rosenheim, Bavaria, Germany
Responsibilities
Entwickle und verantworte die gruppenweite Data- & AI-Platform-Strategie und priorisiere gemeinsam mit Product und Engineering die relevanten Daten, Use Cases und Plattform-Capabilities.
Baue eine gemeinsame, skalierbare Datenplattform mit Datenpipelines, gemeinsamen Domain-Modellen und messbarer Datenqualität über unsere Produkte hinweg auf.
Entwickle unsere Datenbasis für AI Agents weiter und ermögliche einen sicheren, berechtigungsgesteuerten Zugriff über moderne Retrieval-, Search- und Context-Lösungen.
Gestalte offene APIs und agentenfähige Schnittstellen, über die unsere Produkte, Partner und Kunden sicher mit unseren Daten und Plattform-Services arbeiten können.
Baue gemeinsame AI-Platform-Services für unsere Product Teams auf – von Retrieval und Evaluation über Model Routing und Guardrails bis zu Monitoring und Observability.
The Senior Developer, AI is responsible for designing, developing, deploying, and supporting enterprise AI solutions including scalable AI applications, AI agents, and RAG solutions using Databricks.
Responsibilities
Design, build, test, deploy, and support scalable enterprise AI applications, AI agents, and intelligent workflows using Databricks and cloud-native technologies.
Develop AI agents, multi-agent workflows, and RAG solutions by integrating enterprise data, APIs, tools, and business processes to enable automation and decision support.
Create APIs, backend services, integrations, and reusable frameworks while applying software engineering best practices such as CI/CD, automated testing, monitoring, and secure deployment.
Drive solution reliability, performance, Responsible AI compliance, data governance, operational readiness, and continuous improvement through testing, evaluation, and technical reviews.
Partner with business stakeholders, Product Owners, Architects, Data Scientists, Data Engineers, platform teams, and vendors while providing technical guidance, knowledge sharing, and mentoring across AI Delivery PODs.
Design and govern enterprise semantic architectures, ontologies, and knowledge graph platforms to enable AI-ready knowledge systems.
Compensation
The annual salary for this position is between $ 130,000 - $ 160,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Responsibilities
Design and govern enterprise ontologies, semantic models, and knowledge graph architectures
Lead development of business domain models and governed vocabularies
Define and maintain enterprise business glossaries, KPI registries, and governance processes
Architect graph-based knowledge platforms using technologies such as Spanner Graph, Neo4j, Amazon Neptune, TigerGraph, GraphDB, Dataplex, BigQuery, and Vector Search
Partner with engineering, AI, and platform teams to establish governance controls, security standards, and AI architecture guardrails
Requirements
Nice to have: Spanner Graph GQL
Nice to have: knowledge architecture for agentic AI
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