Senior GenAI Engineer

Abacus Medicine

. Design and implement GenAI solutions for real business use cases, from classical NLP approaches to LLM-based applications .

Posted 10/27/2026full-timeBerlin • GermanySeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing GenAI solutions, including RAG pipelines and prompt engineering strategies, while effectively collaborating with cross-functional teams and managing project delivery. Proficient in leveraging cloud platforms and automation tools to enhance AI capabilities and drive innovation.

Highest-signal resume keywords

GenAI Application DevelopmentRAG Pipeline OptimizationPython ProgrammingCloud Platform ExperiencePrompt Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningNatural Language ProcessingContainerizationCI/CD PipelinesVector DatabasesAgent OrchestrationFine-TuningDocument IngestionEmbeddings

Soft Skills

CollaborationCommunicationMentoringProblem-Solving

Tools & Technologies

Azure AI FoundryLangGraphLangChainN8nCloud-Native Tooling

Industry Keywords

AI InitiativesCross-Functional TeamsProduction ContextEmerging AI TechniquesAPIs Integration

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Design and implement GenAI solutions for real business use cases, from classical NLP approaches to LLM-based applications
Build and optimize RAG pipelines, including document ingestion, embeddings, vector search and retrieval quality
Develop prompt engineering strategies and manage prompt lifecycles for production use
Design and implement GenAI workflow automations and integrations using Azure AI Foundry, LangGraph, or similar tools
Rapidly prototype new GenAI use cases, validate ideas with clear success criteria, and iterate before production
Collaborate with Delivery Leads, Data Engineers, Platform Engineers, Data Scientists and business stakeholders
Own solution design and delivery for defined work packages, components or functions within larger AI initiatives
Integrate external data sources and APIs to extend AI capabilities
Bring emerging AI techniques, tools and research back to the team and help evaluate investment opportunities
Help junior engineers grow and review code constructively

Requirements

What you’ll need

Hands-on experience in software engineering or machine learning / deep learning, with a meaningful portion in GenAI or NLP
Strong Python skills
Experience building production-grade GenAI applications, including RAG pipelines, agent orchestration, fine-tuning, prompt engineering and vector databases
Experience working with at least one major cloud platform, such as Azure, AWS or GCP, in a production context
Experience with containerization, CI/CD pipelines and cloud-native tooling
Comfortable working in English in a professional setting, written and verbal
Familiarity with LLM frameworks such as LangChain, LangGraph, or similar is a plus
Familiarity with workflow automation tools such as n8n, Azure AI Foundry, or similar is a plus
Experience working in cross-functional teams with non-technical stakeholders is a plus

Benefits

Comp & perks

Flexible working hours and up to 1 day of home office per week
Annual performance bonus based on company results
30 days of annual leave plus an extra day off on New Year's Eve
Free Germany Ticket for public transport
Subsidized meals on campus, including a daily lunch allowance from Abacus
Access to Wellhub with a monthly contribution towards gyms and fitness classes
OpenUp mental health platform
Complimentary private supplementary health insurance
Free coffee and fresh fruit in the office
Global team events
International, collaborative work environment