AI Solutions Engineer

Required skills: Python, LLM applications, AWS Bedrock, AWS Sagemaker We are looking for an experienced AI Engineer to help our client design and build proof-of-concept and production-ready AI solutions using AWS AI services and modern LLM frameworks. In this role, you will work on agent-based AI systems, scalable LLM applications, and intelligent automation workflows, collaborating closely with engineering and business teams to deliver practical AI-driven solutions. Requirements: Strong experience in Python development Experience building LLM or agent-based applications using LangChain, LangGraph, or similar frameworks Hands-on experience with AWS Bedrock, including models, Agents, and tool/function calling Experience with AWS SageMaker and Bedrock Knowledge Bases Understanding of LLM limitations and practical challenges, including hallucinations, context management, and cost/latency trade-offs Experience designing end-to-end AI systems, including agent workflows and scalable AI services At least one real-world project involving AI agents deployed to production with measurable business impact or automation outcomes Experience creating custom tools/functions for AI agents Familiarity with evaluation, testing, and monitoring of LLM systems Strong communication and problem-solving skills English skills sufficient for technical communication and participation in project discussions Nice to have: Hands-on experience with UiPath platform, including classic RPA and Agentic Automation Experience building and optimizing RAG pipelines (chunking, embeddings, retrieval tuning) Experience integrating AI agents with APIs, databases, and enterprise systems Familiarity with OpenSearch, vector databases, or semantic search solutions Experience with AWS Lambda, API Gateway, and S3 Experience deploying and supporting AI solutions in production environments Familiarity with AI governance, observability, or GenAI security practices Responsibilities: Design and develop LLM and agent-based applications using modern AI frameworks and AWS AI services Build scalable AI workflows and agent orchestration solutions using LangChain, LangGraph, or similar technologies Develop and maintain integrations between AI agents, APIs, databases, and external systems Work with AWS Bedrock services, including models, Agents, and tool/function calling capabilities Support implementation of RAG-based solutions, including embeddings, chunking, and retrieval optimization Create custom tools/functions for AI agents and automation workflows Contribute to architecture decisions for scalable and production-ready AI systems Support evaluation, testing, monitoring, and continuous improvement of LLM-based applications Collaborate with cross-functional teams to prototype and deliver AI-powered automation solutions We offer: Projects for such clients as PayPal, Wargaming, Xerox, Philips, Adidas and Toyota Competitive compensation that depends on your qualification and skills Career development system with clear skill qualifications Flexible working hours aligned to your schedule Options to work remotely