Senior AI Engineer – AWS Bedrock

🕒 Agosto 21

🇺🇦 Ucrânia – Remoto

⏰ Tempo Integral

🟠 Sênior

☁️ Engenheiro de Cloud

👻 Score fantasma 21%

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Automat-it

SiteLinkedInTodas as Vagas

51 - 200 funcionários

💼 Consultoria

📦 Logística

📣 Marketing

Consulting • Logistics • Marketing

A Automat-it é uma parceira AWS Premier completa, que ajuda startups com expertise em DevOps e FinOps e serviços hands-on. Fundada em 2012 pelo CEO Ziv Kashtan, a Automat-it já orientou e apoiou centenas de startups para que aproveitassem a AWS de forma mais inteligente ao longo de sua jornada de crescimento. Especializada em DevOps, serviços de Cloud, DBA, infraestrutura de TI e Performance, a empresa desenvolve soluções em Cloud sob a perspectiva de DevOps, otimizando a performance e a eficiência econômica da Cloud para seus clientes.

Descrição

• 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

🎯 Requisitos

• 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