Senior AI/ML Engineer

Quick Facts

• Role: Senior AI/ML Engineer

Description

Build and maintain RAG pipelines on Amazon Bedrock to ground agent responses in real operational data. Design agent reasoning and prompting strategies for automated, near real-time decisions, and apply MLOps with Amazon SageMaker to keep models reliable in production. Implement multi-step, memory-aware agents using modern agent frameworks, with container-based deployment and embedded AI security (guardrails, PII redaction, IP protection).

Responsibilities

• Build and maintain RAG pipelines using Amazon Bedrock (Claude, Titan Embeddings, Knowledge Bases)
• Design agent reasoning and prompting strategies for automated, near real-time decision-making
• Apply MLOps practices on Amazon SageMaker (pipelines, versioning, evaluation)
• Build multi-step, memory-aware agents using modern agent frameworks (e.g., LangGraph, MCP, AgentCore)
• Deploy container-based agent systems
• Embed AI security practices into agent workflows, including guardrails, PII redaction, and IP protection

Requirements

• Master’s degree in Computer Science, Machine Learning, Data Engineering, or related field
• 5+ years of overall software/ML engineering experience
• 2+ years hands-on GenAI/LLM/agentic experience
• Strong hands-on experience with AWS Cloud
• Hands-on experience with Amazon Bedrock (Claude models, Titan Embeddings, Knowledge Bases)
• Strong current expertise in RAG architecture and prompt engineering
• Experience with OpenSearch vector search
• Experience with Lambda-based ingestion pipelines
• Experience with metadata management alongside vectors
• Advanced experience with Amazon SageMaker (MLOps practices, pipelines, model evaluation)
• Advanced hands-on experience with agent frameworks (e.g., LangGraph/LangChain SDKs, MCP, Amazon AgentCore) in containerized environments
• Working knowledge of long-term agent memory design
• Knowledge of AI security practices (guardrails, PII redaction, IP protection)

Benefits

• Non-corporate work environment among experienced engineers
• Individual growth and development plan with cyclical feedback sessions
• Access to knowledge platforms (e.g., Pluralsight)
• Equipment of your choice
• Financing of conferences, external trainings, and certifications
• Language lessons (English, German, Polish for foreigners)
• LuxMed private medical care
• Weekly Lunch & Learn sessions
• Employee referral program
• Rewards for monthly and yearly success
• Special rewards for years with the company (G-Man)
• Integration activities