- Architectural Leadership : You are the go-to person for all AI/ML infrastructure, Agentic workflows, and RAG technology implementations at Lendingkart.

- Strategic Decisions : Play a crucial role in driving AI product and technology decisions, from model selection (SLMs vs. LLMs) to operational deployments.

- Roadmap & Hiring : Show high levels of ownership in driving the AI roadmap, scalable architectures, and hiring top-tier AI and Data Engineers.

- Code & Design Quality : Actively review code, lead design reviews, and guide architectural discussions for multi-agent systems, prompt engineering frameworks, and MCP server integrations.

- Best Practice Adoption : Drive best practices around Generative AI, fine-tuning methodologies (LoRA/QLoRA), model evaluation (Evals), guardrails, and latency optimization.

- Innovation & Experimentation : Experiment with novel AI frameworks, open-source models, and toolings to continuously drive business efficiency and customer impact.

- Tech Ambassador : Represent Lendingkart in external technical forums and AI conferences as a key technology ambassador.

Preferred candidate profile :

Core AI & Generative AI Expertise (Hands-On) :

- LLMs & SLMs : Practical experience in fine-tuning, serving, and evaluating open-source (Llama, Mistral, Qwen) and proprietary models using LoRA, QLoRA, PEFT, and quantization techniques.

- Agentic AI & Frameworks : Production experience building autonomous, multi-agent frameworks using tools like LangChain, LangGraph, LlamaIndex, AutoGen, or CrewAI.

- MCP Server Integrations : Expertise in integrating Model Context Protocol (MCP) servers/tools to securely expose enterprise context and tools to LLMs.

- RAG Pipelines & Vector DBs : Proven track record of architecting scalable enterprise RAG systems utilizing vector databases (Pinecone, Milvus, Qdrant, PGVector) with advanced retrieval techniques (Hybrid Search, GraphRAG, Query Rewriting, Re-ranking).

- Prompt Engineering & Evals : Mastery of advanced prompt strategies (Chain-of-Thought, ReAct, Few-Shot) and evaluation/observability stacks (Ragas, TruLens, DeepEval, LangSmith, Langfuse).

Engineering, Cloud & Security :

- Languages & Frameworks : Highly proficient in Python (PyTorch, Hugging Face, vLLM, Ollama, FastAPI) and backend systems in Golang, Java, or JavaScript.

- Cloud & Cloud-Native : Experience with AWS (Bedrock, SageMaker) and/or GCP (Vertex AI), alongside containerization (Docker, Kubernetes).

- AI Security & Guardrails : Hands-on knowledge of AI guardrails (NeMo Guardrails, Llama Guard, OWASP LLM Top 10), data privacy, PII masking, and red-teaming.

- DevOps & Infrastructure : Experience with CI/CD, Infrastructure as Code (Terraform), and LLMOps monitoring/alerting.