Senior AI Engineer – AWS Bedrock

This is a fully remote position, open to applicants in Ukraine.

📋 Description

• Develop and implement production-ready Generative AI systems on AWS, utilizing Amazon Bedrock, AgentCore, RAG systems, intelligent document processing, voice AI, and LLM-driven services.

• Design and execute AI agents leveraging Amazon Bedrock AgentCore, AWS Strands, MCP, and contemporary orchestration frameworks tailored for customer solutions.

• Collaborate with Solution Architects, DevOps, and client teams to transform discovery workshops, ideas, and POCs into operational AI systems.

• Assess and select LLMs based on criteria such as accuracy, latency, cost, and client specifications.

• Create reusable AI components and deployment frameworks for upcoming customer projects.

• Deploy, monitor, and enhance ML/LLM systems in production, prioritizing performance, cost-effectiveness, and reliability.

• Utilize AWS services including Bedrock, OpenSearch, Lambda, S3, DynamoDB, SageMaker, and CloudWatch.

• Adapt existing ML or GenAI code for production settings.

• Enhance system quality by improving retrieval performance, output consistency, and evaluation methodologies.

• Take ownership of projects from inception to completion as the lead engineer in a dynamic, project-driven environment.

⛳️ Requirements

• Proven hands-on experience in building and deploying AI / GenAI systems in a production environment.

• Extensive hands-on experience with AWS beyond model invocation, covering infrastructure, IAM, serverless solutions, networking, storage, monitoring, and production deployments using Amazon Bedrock.

• Practical experience in developing RAG systems, including retrieval logic, vector databases, and enhancements to output quality.

• Deep understanding of contemporary LLM ecosystems, encompassing commercial and open-source models, their advantages and disadvantages, deployment alternatives, and real-world applications.

• Proficient in Python with a solid grasp of backend system design.

• Experience in designing multi-agent systems or intricate orchestration workflows.

• Familiarity with vector databases such as OpenSearch, pgVector, or Pinecone.

• Ability to thrive in fast-paced environments with short project timelines.

• Excellent communication skills with the capability to engage directly with clients and cross-functional teams.

• Proficient in articulating technical choices, limitations, and trade-offs in both written and spoken English.

• Hands-on experience with Amazon Bedrock Knowledge Bases, AgentCore, Agents, AWS Strands, or MCP is a significant advantage.

• Experience in selecting, assessing, and optimizing LLMs for quality, latency, and cost efficiency.

• Familiarity with Infrastructure as Code tools such as Terraform, CloudFormation, or AWS CDK, Docker, Kubernetes, and CI/CD pipelines is a considerable advantage.

• Knowledge of speech-to-text, text-to-speech, or Voice AI technologies is a plus.

• A background in Machine Learning or Data Science, including model training or fine-tuning, is advantageous.

• CV submitted in English.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional development and continuous learning.

• Flexible working hours and remote work options.

• A collaborative and innovative work environment.

• Health insurance and wellness programs.