Job Title: AI Lead
Location: Kalyani Nagar, Pune
Experience: 4-6 years
Employment Type: Full- Time
Role Summary:
Design and lead the implementation of enterprise AI solutions – spanning Classic ML, Generative AI, and
Agentic AI – on AWS or Azure, defining AI strategy, architecture patterns, and responsible AI practices for
customers.
Key Responsibilities:
- Design end-to-end AI or ML solution architectures on cloud platforms — AWS (SageMaker, Bedrock,
- Rekognition, Comprehend) or Azure (Azure ML, Azure OpenAI Service, Cognitive Services)
- Define AI strategy and roadmaps aligned with customer business objectives covering Classic ML,
GenAI, and Agentic AI - Architect GenAI solutions using foundation models, RAG patterns, fine-tuning strategies, and multi
agent or agentic frameworks - Design agentic AI architectures including tool use, planning, memory, and orchestration patterns
- Design MLOps pipelines for model training, evaluation, deployment, and monitoring
- Establish responsible AI practices including bias detection, explainability, guardrails, and governance
- Evaluate and recommend AI or ML services, frameworks, and tools for specific use cases
- Lead technical workshops, PoCs, and architecture reviews for AI initiatives
- Collaborate with Data Architects and Data Engineers to ensure data readiness for AI workloads
Required Qualifications:
- 5 – 10 years of experience in AI or ML architecture, data science, or ML engineering
- Deep knowledge of ML frameworks (PyTorch, TensorFlow, scikit-learn)
- Hands-on experience with cloud AI or ML services — AWS (SageMaker, Bedrock) or Azure (Azure ML,
Azure OpenAI Service) - Strong understanding of LLMs, foundation models, prompt engineering, RAG architectures, and
agentic AI patterns - Experience designing MLOps pipelines and model lifecycle management
- Strong understanding of data preparation, feature engineering, and model evaluation
Preferred Qualifications:
Cloud certification — AWS Machine Learning Specialty or Azure AI Engineer Associate
- Experience with multi-agent AI systems and agentic orchestration frameworks (e.g., LangChain,
LangGraph, AutoGen, CrewAI, Amazon Bedrock Agents) - Knowledge of responsible AI frameworks and AI governance
- Multi-cloud AI experience