AI Lead

Teleglobals

Pune District

On-site

INR 3,000,000 - 4,200,000

Full time

14 days+

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Job summary

Teleglobals seeks an AI Lead to design and lead enterprise AI solutions spanning Classic ML, Generative AI, and Agentic AI on AWS or Azure. You will define AI strategy, architecture patterns, and responsible AI practices for customers.

You will craft end-to-end AI architectures on cloud platforms, lead PoCs, and drive architecture reviews while collaborating with data teams to ensure data readiness for AI workloads.

Qualifications

  • 4-6 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 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.

Responsibilities

  • Design end-to-end AI or ML solution architectures on cloud platforms — AWS or Azure.
  • Define AI strategy and roadmaps aligned with customer objectives covering Classic ML, GenAI, and Agentic AI.
  • Architect GenAI solutions using foundation models, RAG patterns, fine-tuning, and multi-agent frameworks.
  • Design agentic AI architectures including tool use, planning, memory, and orchestration patterns.
  • Design MLOps pipelines for model training, evaluation, deployment, and monitoring.
  • 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.

Skills

AI architecture
Cloud platforms
LLMs / GenAI
MLOps
Prompt engineering

Tools

PyTorch
TensorFlow
scikit-learn

Job description

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,
  • 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
  • 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:
  • 4-6 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
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