Role Purpose

Design and deliver enterprise AI, Machine Learning and Generative AI solutions on Azure, AWS or GCP. The candidate must combine practical engineering depth with cloud architecture, Python, responsible AI, governance and measurable business outcomes.

Key Responsibilities

- Design AI/ML and GenAI solution architecture on Azure, AWS or GCP.

- Build data preparation, training, evaluation, deployment and monitoring workflows.

- Develop NLP, machine-learning, LLM, RAG, agent or conversational AI solutions.

- Use Python and relevant ML or LLM frameworks to implement production services.

- Select models and design prompt, retrieval, embedding, vector-search and grounding patterns.

- Define responsible-AI controls for privacy, security, fairness, explainability, safety and human oversight.

- Implement MLOps/LLMOps, observability, evaluation, cost controls and model lifecycle governance.





- For architect roles, define enterprise AI strategy, reference architecture and adoption roadmap.

Mandatory Skills

- Artificial Intelligence and Machine Learning

- Generative AI and LLMs

- Python

- NLP

- RAG and vector search

- Azure, AWS or GCP

- MLOps / LLMOps

- AI Governance and Responsible AI

- Enterprise AI Architecture

- APIs and integration

Preferred Tools and Platforms

- Azure AI Foundry / Azure OpenAI / Azure Machine Learning

- Amazon Bedrock / SageMaker

- Google Vertex AI / Gemini

- Python, PyTorch, TensorFlow, scikit-learn

- LangChain, LlamaIndex or Semantic Kernel

- Azure AI Search, Pinecone, Weaviate, pgvector or equivalent

- MLflow, prompt/model evaluation and monitoring tools

📌 Artificial Intelligence Architect_A (Bengaluru)
🏢 Infosys
📍 Bengaluru