Key skills
AWSDynamoDBPythonPyTorchTensorflowAIMLGenerative AILLMOpenAIClaudeLlamaRAGLangChainAgenticTensorFlowHugging FaceLangGraphPineconeAnalyticsGitHub ActionsLambdaS3CloudWatchSageMakerBedrockAPI GatewayGitHubCI/CD
About this role
Role Overview
- Develop agentic AI workflows using LangChain/LangGraph with custom tools, memory, decision logic, and MCP integrations.
- Implement LLM applications with advanced prompt engineering (structured outputs, function calling, context management) and build RAG pipelines with vector databases.
- Build and deploy event-driven AI services on AWS using Bedrock, SageMaker, Lambda, EventBridge, Step Functions, API Gateway, DynamoDB, and S3.
- Write clean, testable Python code; create unit/integration tests; and package solutions with CI/CD pipelines (GitHub Actions).
- Monitor and optimize AI application performance through logging, metrics, token usage, and cost management.
- Integrate AI services with APIs, backend systems, and databases to ensure secure and reliable data flow.
- Contribute to document AI and predictive analytics models for information extraction, classification, and forecasting.
- Fine-tune Hugging Face Transformer models (BERT, RoBERTa, LayoutLM, DistilBERT) and train neural networks (PyTorch/TensorFlow) for supervised tasks.
- Implement data preprocessing and annotation workflows for training and evaluation.
- Work with OCR and text-processing tools (AWS Textract, Tesseract) for semi-structured/unstructured documents.
Requirements
- 5+ years in software engineering, including 3+ years in python, AI/ML or Generative AI systems.
- Proven development experience with LLM frameworks (LangChain, LangGraph) and LLM APIs (Claude, OpenAI, Llama, Titan).
- Hands-on experience with AWS Bedrock and SageMaker for AI/ML workloads.
- Strong Python skills (async, data structures, optimization).
- Practical experience with vector databases (Pinecone, ChromaDB, FAISS, OpenSearch) for RAG implementations.
- Familiarity with event-driven AWS services (Lambda, EventBridge, Step Functions, API Gateway, DynamoDB, S3, CloudWatch).
- Exposure to document AI and predictive analytics, including Hugging Face Transformers, classification, and extraction pipelines.
- Understanding of data preprocessing and OCR workflows for document pipelines.
Tech Stack
- AWS
- DynamoDB
- Python
- PyTorch
- Tensorflow