Role Summary

Lead architecture, development and deployment of enterprise AI, Generative AI, Agentic AI and intelligent applications. Combine AI engineering, cloud

architecture, full-stack development and enterprise solution design.

Key Responsibilities

- Architect secure, scalable AI platforms and enterprise applications; integrate AI with backend services, frontend applications and enterprise systems.

- Build LLM, RAG, AI-agent and multi-agent solutions; define architecture, frameworks, technical roadmaps and engineering standards.

- Lead architecture reviews and design discussions; mentor AI engineers, data scientists and full-stack teams.

- Apply prompt engineering, knowledge graphs, semantic search, vector databases, fine-tuning, model evaluation, function calling and MCP.

- Build enterprise solutions using .NET Core/ASP.NET Core, C#, EF Core, microservices, REST APIs, FastAPI, Angular and TypeScript.

- Lead PoCs, customer workshops and demonstrations; translate business needs into AI solutions and oversee deployment, monitoring and improvement.

- Establish responsible AI governance, observability, privacy, security, explainability and compliance; optimize performance, latency, reliability and cost.

Required Technical Skills

- Expert Python; PyTorch, TensorFlow,



Hugging Face Transformers, Scikit-learn and FastAPI.

- LLMs and GenAI: prompt engineering, RAG, fine-tuning/evaluation, AI agents, multi-agent systems, function calling and MCP.

- Frameworks: one or more of LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen or Semantic Kernel.

- Vector stores/search: Pinecone, Azure AI Search, ChromaDB, Weaviate, Milvus or FAISS.

- Cloud: Azure, Azure OpenAI, Azure AI Foundry, Azure ML, AWS Bedrock/SageMaker or Google Vertex AI.

- DevOps/AI Ops: Docker, Kubernetes, Git, CI/CD, MLflow, Azure DevOps, GitHub Actions, MLOps and LLMOps.

- Enterprise full-stack development and integration across .NET, C#, Angular, TypeScript, HTML5 and CSS3.

Preferred Qualifications & Skills

- Bachelor’s/Master’s in Computer Science, AI, Data Science or related field; relevant Azure, AWS or Google AI certifications preferred.

- Enterprise architecture and customer-facing consulting experience; knowledge of AI security, governance and responsible AI.

- Robust leadership, mentoring, analytical, communication, stakeholder and presentation skills.

Pay: ₹2,300,000.00 - ₹3,200,000.00 per year

Work Location: In person

📌 AI Solutions Architect (Bengaluru)
🏢 Kalpita Technologies
📍 Bengaluru