Senior AI Engineer – AWS Bedrock

🕒 August 21

🇺🇦 Ukraine – Remote

⏰ Full Time

🟠 Senior

☁️ Cloud Engineer

👻 Ghost score 32%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Automat-it

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Automat-it is an all-in AWS Premier partner empowering startups with DevOps & FinOps expertise and hands-on services. Founded in 2012 by CEO Ziv Kashtan, Automat-it has guided and supported hundreds of startups to leverage AWS smarter throughout their growth journey. Specializing in DevOps, Cloud services, DBA, IT infrastructure, and Performance, they build cloud solutions from the DevOps perspective to optimize cloud performance and economics for their customers.

📋 Description

• Build and deliver production-ready GenAI systems on AWS, including Amazon Bedrock, AgentCore, RAG systems, intelligent document processing, voice AI, and LLM-powered services • Design and implement AI agents using Amazon Bedrock AgentCore, AWS Strands, MCP, and modern orchestration frameworks • Work with Solution Architects, DevOps, and customer teams to turn discovery workshops, ideas, and POCs into production-ready AI systems • Evaluate and select LLMs based on accuracy, latency, cost, and customer requirements • Build reusable AI components and deployment patterns for future customer projects • Deploy, monitor, and improve ML/LLM systems in production, focusing on performance, cost, and reliability • Work with AWS services including Bedrock, OpenSearch, Lambda, S3, DynamoDB, SageMaker, and CloudWatch • Adapt existing ML or GenAI code into production environments • Improve system quality, including retrieval performance, output consistency, and evaluation approaches • Own projects as the main engineer in a fast-paced, project-based environment

🎯 Requirements

• Strong hands-on experience building and deploying AI / GenAI systems in production • Strong hands-on AWS experience beyond model invocation, including infrastructure, IAM, serverless services, networking, storage, monitoring, and production deployments using Amazon Bedrock • Experience building RAG systems in practice, including retrieval logic, vector databases, and output quality improvements • Strong understanding of modern LLM ecosystems, including commercial and open-source models, their trade-offs, deployment options, and production use cases • Strong Python skills and a good understanding of backend system design • Experience designing multi-agent systems or more complex orchestration workflows • Experience with vector databases such as OpenSearch, pgVector, or Pinecone • Comfort working in fast-moving environments with short project cycles • Strong communication skills and ability to work directly with clients and cross-functional teams • Ability to clearly explain technical decisions, limitations, and trade-offs in English, written and spoken • Hands-on experience with Amazon Bedrock Knowledge Bases, AgentCore, Agents, AWS Strands, or MCP is a strong advantage • Experience selecting, evaluating, and optimizing LLMs for quality, latency, and cost • Experience with Infrastructure as Code, including Terraform, CloudFormation, or AWS CDK, is a strong advantage • Experience with Docker, Kubernetes, and CI/CD pipelines is a strong advantage • Experience with speech-to-text, text-to-speech, or Voice AI is an advantage • Background in Machine Learning or Data Science, including model training or fine-tuning, is an advantage • Submit CV in English