Automotive | Aviation | Manufacturing | Insurance
Senior
Software Engineering
Tech stack
AWS
Amazon Bedrock (Claude, Titan Embeddings, Knowledge Bases)
RAG Architecture & Prompt Engineering
Amazon SageMaker
Agent Frameworks (LangGraph/LangChain SDKs, MCP, AgentCore)
At Grape Up, we transform businesses by unlocking the potential of AI and data through innovative software solutions.
We partner with industry leaders in the automotive and aviation to build sophisticated Data & Analytics platforms that support production machine learning and AI use cases. Our solutions provide comprehensive capabilities spanning data storage, management, advanced analytics, machine learning, enabling enterprises to accelerate innovation and make trusted, data-driven decisions.
Responsibilities
- Build and maintain RAG pipelines using Amazon Bedrock (Claude, Titan Embeddings, Knowledge Bases) to ground agent responses in real operational data
- Design and implement agent reasoning and prompting strategies that support automated, near real-time decision-making
- Apply MLOps practices on Amazon SageMaker – pipelines, versioning, evaluation – to keep models reliable as they move into production
- Build multi-step, memory-aware agents using modern agent frameworks (e.g., LangGraph, MCP, AgentCore) with container-based deployment
- Embed AI security practices – guardrails, PII redaction, IP protection – into every agent workflow, including any automated output that reaches an external party
Requirements
- Master’s degree in computer science, Machine Learning, Data Engineering or a related field
- 5+ years of overall software/ML engineering experience and 2+ hands-on GenAI/LLM/agentic experience
- Strong, hands-on experience with AWS Cloud
- Hands-on experience with Amazon Bedrock (including Claude models, Titan Embeddings, and Knowledge Bases)
- Strong, current expertise in RAG architecture and prompt engineering (including OpenSearch vector search, Lambda-based ingestion pipelines, and metadata management alongside vectors)
- Advanced experience with Amazon SageMaker, covering MLOps practices, pipelines, and model evaluation
- Advanced, hands-on experience with agent frameworks such LangGraph/LangChain SDKs, including MCP and Amazon AgentCore in containerized environments (with working knowledge of long-term agent memory design)
- Knowledge of AI security practices, including guardrails, PII redaction, and IP protection
- Very good command of English and Polish, both written and spoken (B2+/C1) – daily collaboration within the team takes place in English
Nice to have
- CI/CD skills for production GenAI and agentic workloads, with demonstrable, current hands-on knowledge of modern tooling
- Experience with containerized ML workloads using Docker and Kubernetes
- Experience with infrastructure-as-code (Terraform, CloudFormation, or similar)
Recruitment owner
Klaudia Jazowska
Senior AI/ML Engineer
apply now
Benefits
Employee referral
Knowledge platforms
Equipment
Integration activities
Employee referral
Knowledge platforms
Equipment
Integration activities
Lunch & Learn
In-house Tech Up
Language lessons
Lunch & Learn
In-house Tech Up
Language lessons
Conferences & training
Development plan
Feedback sessions
Business travel opportunities
Conferences & training
Development plan
Feedback sessions
Business travel opportunities
Check out the next steps of your recruitment process
Application
Send us your CV through the application form.
HR & Manager interview
Let’s talk about your experience and expectations, and what this role has in store for you.
Task
Put your skills to the test with a practical challenge.
Offer
We’re excited to welcome you onboard! Let’s discuss the details.
Feedback
If you’re not lucky this time, we’ll tell you what you can improve to join us in the future.
