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· Design, develop, and deploy LangGraph-based agentic systems that orchestrate LLM-driven tools and workflows.
· Build and integrate modular AI agents capable of real-world task execution in cloud-native environments.
· Utilize AWS services such as Lambda, Step Functions, Bedrock, S3, ECS/Fargate, DynamoDB, and API Gateway to support scalable, serverless infrastructure.
· Write production-grade Python code, following best practices in software design, testing, and documentation.
· Build robust CI/CD pipelines and advocate for DevOps and Infrastructure as Code (IaC) practices using tools like CDK or Terraform.
· 5+ years of experience as a Software Engineer, with at least 2 years in AI/ML or LLM-centric development.
· Proven track record with LangGraph, LangChain, or similar orchestration frameworks.
· Hands-on experience building and deploying applications on AWS, particularly using Lambda, Fargate, S3, Step Functions, and DynamoDB.
· Familiarity with AWS Bedrock is a plus.
· Strong understanding of agentic patterns, prompt chaining, tool calling, and memory/state management in LLM applications.
· Solid experience with unit and integration testing, CI/CD, and GitOps practices.
Preferred Qualifications
· Experience designing and scaling multi-agent systems or tool-augmented LLM workflows.
· Familiarity with secure cloud development practices and IAM role design.
· Understanding of LLM fine-tuning, embeddings, vector stores (e.g., Pinecone, FAISS, OpenSearch).
· Exposure to contact centre automation, conversational agents, or RAG pipelines.
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