Описание
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 (
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