EPAM Systems
1 week ago
Lead GenAI Engineer
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Company information
- Company
- EPAM Systems
- Location
- Mexico Mexico
- Posted
- 1 week ago
Job description
We are seeking a Lead GenAI Engineer to architect, develop, and manage agentic AI solutions on Amazon Bedrock AgentCore as part of a contact center transformation initiative. The consultant will lead the implementation of multi-agent workflows, craft LLM-driven conversational experiences, and connect these solutions with Amazon Connect.
Responsibilities
- Architect and build multi-agent workflows on Amazon Bedrock AgentCore to coordinate complex, automated business operations
- Develop agentic AI systems that leverage tool use, memory handling, and orchestration techniques to support autonomous, context-driven agent actions
- Craft prompt engineering approaches and context assembly methods tailored for large-scale production environments
- Connect agentic AI functionality with Amazon Connect contact center workflows to strengthen customer interaction automation
- Build LLM-driven applications powered by Amazon Bedrock foundation models to deliver robust, scalable generative AI features
- Construct RAG (Retrieval-Augmented Generation) pipelines and knowledge base connections to keep model outputs accurate and current
- Create and launch conversational AI experiences for customer-facing platforms, ensuring smooth and intuitive interactions
- Establish guardrails, safety mechanisms, and compliance protocols to support responsible and secure AI usage
- Roll out solutions through AWS serverless offerings, such as Lambda, Step Functions, and API Gateway, to construct efficient and scalable architectures
- Develop evaluation frameworks to consistently monitor model and prompt performance and confirm readiness for deployment
- Set up observability tools and fine-tune solutions for optimal cost and latency in live environments
- Partner with customer stakeholders to collect requirements, incorporate feedback, and refine solutions across the project timeline
Requirements
- At least 5 years of relevant experience in AI/ML engineering positions
- A minimum of one year of experience leading and overseeing teams
- Practical experience with Amazon Bedrock for creating and launching generative AI applications
- Demonstrated background in generative AI/LLM application development, covering prompt design, foundation model integration, and building production-ready AI features
- Track record of constructing agentic and multi-agent workflows that support autonomous task completion, tool integration, and coordination across multiple AI agents
- Advanced Python skills for building ML/AI applications, encompassing data handling, model integration, and API creation
- Strong grasp of AWS serverless architecture, including tools like Lambda, Step Functions, and API Gateway, for developing scalable and dependable cloud-based solutions
- Strong English communication abilities (B2 level or above)
Nice to have
- Background in Amazon Connect integration for developing and improving contact center automation and customer service processes
- Exposure to Bedrock AgentCore for building and overseeing sophisticated multi-agent orchestration and agentic AI systems
- Understanding of MLOps/LLMOps methodologies for handling the complete ML/AI model lifecycle, from deployment and monitoring to versioning and ongoing enhancement in live settings
Required skills
- customer service
- compliance
- monitoring
- team leadership
- generative ai
- python
- llm
- prompt engineering
- lambda
- genai
- step functions
- english communication
- conversational ai
- large language models
- observability tools
- api gateway
- cost optimization
- rag
- deployment
- agentic ai
- tool integration
- mlops
- orchestration
- ai engineer
- knowledge base
- data handling
- foundation models
- b2 level
- aws serverless
- cloud-based solutions
- scalable architectures
- versioning
- llmops
- evaluation frameworks
- ai applications
- retrieval-augmented generation
- amazon connect
- model performance
- guardrails
- multi-agent workflows
- tool use
- amazon bedrock
- latency optimization
- multi-agent orchestration
- customer-facing platforms
- api creation
- live environments
- model integration
- safety mechanisms
- ai/ml engineering
- agentcore
- model lifecycle
- contact center transformation
- bedrock agentcore
- contact center automation
- prompt performance
- context assembly
- ml applications
- memory handling
- production-ready ai
- autonomous task completion
- aws serverless architecture
- amazon connect integration
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