Description

Key Responsibilities

1. Lead end-to-end design and delivery of production-grade AI/ML solutions including RAG pipelines, LLM applications and extraction systems.
2. Architect and develop robust, scalable AI/ML services in Python.
3. Develop and optimize AI-driven extraction workflows using document parsing, chunking, embeddings, RAG and LLM-based extraction.
4. Deploy and scale AI models on AWS and Azure including SageMaker, Bedrock and Azure AI Foundry.
5. Build and maintain CI/CD pipelines using GitHub Actions, Azure DevOps, Docker and Kubernetes.
6. Define evaluation frameworks including precision, recall, F1 and field-level accuracy.
7. Partner with Product, Data Engineering and Platform teams.
8. Mentor team members and share knowledge.
9. Research advancements in NLP, LLMs and extraction techniques.
10. Follow Agile practices and drive automation.

Mandatory Requirements

• 3+ years professional AI/ML engineering experience delivering production-grade AI systems.
• Strong Python, SQL, Scikit-Learn, Pandas, NumPy, PyTorch/TensorFlow and REST APIs.
• Hands-on experience building and deploying production ML/LLM solutions including RAG, document parsing, extraction and text processing.
• Strong NLP and extraction-focused ML depth: transformers, embeddings, vector databases, RAG, LLM integrations and agentic workflows.
• AWS and Azure experience including AI Foundry, Azure OpenAI, SageMaker, Bedrock and Lambda.
• Experience with LangGraph, LangChain and CrewAI.
• MLOps experience with MLflow, Weights & Biases, model versioning, registry, retraining and CI/CD.
• Docker and Kubernetes experience.
• AI evaluation and observability experience including Prometheus, Grafana and SLOs.
• Experience leading projects, managing deliverables and mentoring.
• Bachelor's or Master's degree in CS, Engineering, Data Science, Mathematics or Statistics.
• B2B Technology, Consulting or B2B Software company background

Key Skills

Education

Bachelor's or Master's degrees