Key Responsibilities
• Design, develop, and implement AI / GenAI solutions using Python
• Build production-ready AI components, including:
- Data ingestion & preprocessing pipelines
- Prompt engineering and orchestration layers
- Retrieval-Augmented Generation (RAG) pipelines
- API-based AI services and microservices
• Integrate and deploy models into production environments
• Develop LLM-based workflows (agents, tools, embeddings)
• Perform data transformation and feature engineering
• Optimize, debug, and scale AI systems for performance and reliability
Cloud & AI Ecosystems
• AWS: Bedrock, SageMaker, Lambda, API Gateway, S3, OpenSearch, Amazon Q
• Azure: Azure OpenAI, Azure AI Studio, Cognitive Services, Azure ML, Functions
Required Skills
• Strong hands-on Python development experience (must-have)
• Proven experience building and deploying AI/ML/GenAI solutions
• Expertise in:
- LLMs, prompt engineering, RAG, agents, embeddings
- REST APIs, SDK integrations, microservices
- Cloud-native development (AWS and/or Azure)
Experience
• 10–15+ years of overall experience
• 5+ years delivering AI/ML solutions in production
• Client-facing / onshore experience preferred
Nice to Have
• FastAPI / Flask experience
• Knowledge of vector databases or document intelligence
• AWS / Azure AI certifications