Automat-it is an AWS Premier Partner and Managed Services Provider focused on startups. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to help startups grow and optimize cloud performance and costs. We work across EMEA and the US. We are seeking a Senior AI Engineer to join our team and work directly with startup Data Science and R&D teams. This is a hands-on, delivery-focused role where you will own projects end-to-end, from design to production deployment. The role focuses on building production-grade GenAI systems on AWS, including RAG pipelines, agent-based workflows, and LLM-powered backend services. This is not a pure research or model training role; it’s about designing and shipping reliable systems under real constraints. Work location: remote from Ukraine.
Automat-it is an AWS Premier Partner and Managed Services Provider focused on startups. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to help startups grow and optimize cloud performance and costs. We work across EMEA and the US. We are seeking a Senior AI Engineer to join our team and work directly with startup Data Science and R&D teams. This is a hands-on, delivery-focused role where you will own projects end-to-end, from design to production deployment. The role focuses on building production-grade GenAI systems on AWS, including RAG pipelines, agent-based workflows, and LLM-powered backend services. This is not a pure research or model training role; it’s about designing and shipping reliable systems under real constraints. Work location: remote from Ukraine.
Key Responsibilities: Build and deliver production-ready GenAI systems on AWS, including RAG pipelines and retrieval logic; design and implement agent-based or multi-step workflows for real use cases; work closely with Solution Architects, DevOps, and client teams to turn ideas into scalable systems; deploy, monitor, and improve ML/LLM systems in production, focusing on performance, cost, and reliability; work with AWS services such as Bedrock, OpenSearch, Lambda, S3, DynamoDB, SageMaker, and CloudWatch; adapt existing ML or GenAI code into production environments when needed; continuously improve system quality, including retrieval performance, output consistency, and evaluation approaches; operate in a fast-paced, project-based environment w
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Key Responsibilities: Build and deliver production-ready GenAI systems on AWS, including RAG pipelines and retrieval logic; design and implement agent-based or multi-step workflows for real use cases; work closely with Solution Architects, DevOps, and client teams to turn ideas into scalable systems; deploy, monitor, and improve ML/LLM systems in production, focusing on performance, cost, and reliability; work with AWS services such as Bedrock, OpenSearch, Lambda, S3, DynamoDB, SageMaker, and CloudWatch; adapt existing ML or GenAI code into production environments when needed; continuously improve system quality, including retrieval performance, output consistency, and evaluation approaches; operate in a fast-paced, project-based environment w
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Based on: Senior AI Engineer
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