Senior AI/ML Engineer

Grape Up

Polska

Hybrid

PLN 180,000 - 260,000

Full time

4 hours ago

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Job summary

Grape Up is seeking a Senior AI/ML Engineer to advance AI and data solutions for automotive and aviation sectors. You will design and build multi-step, memory-aware agents grounded in real operational data using Amazon Bedrock and SageMaker, while implementing robust RAG architectures and security practices.

You will collaborate across English and Polish-speaking teams, contribute to model evaluation, pipelines, and deployments in containerized environments, and drive production-grade GenAI

Qualifications

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 (Claude, Titan Embeddings, Knowledge Bases).
Strong, current expertise in RAG architecture and prompt engineering (OpenSearch vector search, Lambda ingestion pipelines, metadata management alongside vectors).
Advanced experience with Amazon SageMaker, covering MLOps, pipelines and model evaluation.
Advanced, hands-on experience with LangGraph/LangChain SDKs, MCP and Amazon AgentCore in containers.
Knowledge of AI security practices including guardrails and PII/IP protection.
Very good command of English and Polish (B2+/C1).

Responsibilities

Build and maintain RAG pipelines using Amazon Bedrock to ground agent responses.
Design and implement agent reasoning and prompting strategies for real-time decision-making.
Apply MLOps practices on SageMaker to keep models reliable in production.
Build multi-step, memory-aware agents with container-based deployment.
Embed AI security practices into every agent workflow and outputs.

Skills

GenAI/LLM

AWS Cloud

RAG architecture

Agent frameworks

Bilingual English/Polish

Education

Master’s degree in CS/ML

Tools

Amazon Bedrock

SageMaker

OpenSearch

Docker

Kubernetes

Job description

Automotive | Aviation | Manufacturing | Insurance

Seniority

Senior

Department

Software Engineering

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)

Benefits