Posted on: 13-10-2026

Experience: 8-12 years

India-Bengaluru

Job ID #1002279

Role Requirements

- Skills: Python, PyTorch, TensorFlow, Hugging Face Transformers, Scikit-learn, FastAPI, REST APIs, Large Language Models, OpenAI, Azure OpenAI, Claude, Gemini, Llama, Mistral, Prompt Engineering, RAG, AI Agents, Multi-Agent Systems, Function Calling, MCP, LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, Knowledge Graphs, Semantic Search, Pinecone, Azure AI Search, ChromaDB, Weaviate, Milvus, FAISS, Microsoft Azure, Azure AI Foundry, Azure Machine Learning, AWS Bedrock, Amazon SageMaker, Google Vertex AI, Docker, Kubernetes, Git, CI/CD, MLflow, Azure DevOps, GitHub Actions, MLOps, LLMOps
- Design and architect scalable AI, Generative AI, and Agentic AI solutions for enterprise customers.
- Develop AI-powered applications using LLMs, Retrieval-Augmented Generation (RAG), AI Agents, and Multi-Agent systems.
- Build cloud-native, secure, and highly scalable AI platforms and APIs.
- Lead technical design discussions, architecture reviews, and solution planning.
- Mentor and guide AI engineers, data scientists, and full-stack development teams.
- Establish engineering standards, coding best practices, and AI governance frameworks.
- Drive architecture decisions and technology roadmaps for AI initiatives.
- Develop intelligent applications using LLMs, Prompt Engineering, RAG pipelines, AI Agents, Multi-Agent Frameworks, Knowledge Graphs, Semantic Search, and Vector Databases.




- Build production-ready AI solutions using MLOps and LLMOps best practices.
- Optimize AI model performance, latency, scalability, and operational cost.
- Work closely with product owners, business analysts, customers, and delivery teams to translate business challenges into AI-driven solutions.
- Lead proof-of-concepts (PoCs), customer workshops, and AI solution demonstrations.
- Ensure successful deployment, monitoring, and continuous improvement of AI systems.
- Establish AI governance, responsible AI practices, model monitoring, and compliance standards.
- Ensure data privacy, security, explainability, and ethical AI implementation.
- Implement AI observability, evaluation frameworks, and continuous model optimization.
- Have a minimum of 5+ years in AI/ML and Generative AI, with 3+ years in technical leadership.
- A Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field is preferred.
- Azure AI Engineer, Azure AI Foundry, AWS Machine Learning, or Google Cloud AI certifications are highly desirable.
- Experience in enterprise solution architecture and customer-facing consulting roles is preferred.
- Exposure to AI security, governance, Responsible AI, and AI compliance frameworks is preferred.
- Demonstrate strong leadership, mentoring, analytical, problem-solving, communication, and stakeholder management skills.
- Have a customer-focused mindset with robust presentation and consulting skills.

📌 AI Engineer - Lead (Bengaluru)
🏢 Kalpita Technologies
📍 Bengaluru