Assistant Manager – 3 to 5 years' experience in Python, Agentic AI

Posted 4ds ago

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Job Description

Assistant Manager responsible for developing AI workflows and applications using Python. Engaging in advanced AI/ML tasks and building event-driven services on AWS at WNS.

Responsibilities:

  • 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-

Requirements:

  • 5+ years in software engineering, including 3+ years in 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.

Benefits:

  • Employees can work remotely

WNS

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