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