Technical Architect - AI

Lendingkart; Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

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Job summary

Lendingkart is seeking a senior AI/ML architect to lead the architecture of AI infrastructure, agentic workflows, and RAG technology. You will own critical decisions around model selection and operational deployments, shaping the AI roadmap and scalable architectures.

In this role you will review code, drive design discussions for multi-agent systems, and mentor AI and data engineers while evangelizing best practices in Generative AI, guardrails, and latency optimizations across the stack.

Qualifications

• Hands-on experience fine-tuning and serving open-source LLMs using LoRA/QLoRA/PEFT.
• Experience building autonomous multi-agent frameworks.
• Expertise integrating MCP servers/tools for enterprise context.
• Proven RAG system architecture with vector DBs and advanced retrieval.
• Mastery of prompt engineering and evaluation/observability stacks.

Responsibilities

• Architect AI/ML infrastructure, agentic workflows, and RAG tech.
• Drive AI product and technology decisions from models to deployments.
• Own AI roadmap, architecture, and hiring for AI/data engineers.
• Lead code/design reviews for multi-agent systems and MCP integrations.
• Promote best practices for Generative AI, guardrails, and latency optimization.
• Experiment with new AI frameworks to improve business impact.
• Represent Lendingkart in external technical forums.

Skills

LLMs & SLMs

Agentic AI Frameworks

MCP Server Integrations

RAG Pipelines & Vector DBs

Prompt Engineering

Model Evaluation & Evals

Python & ML Frameworks

Cloud & DevOps

AI Security & Guardrails

Tools

LangChain

LangGraph

LlamaIndex

AutoGen

CrewAI

Pinecone

Milvus

Qdrant

PGVector

Job description

Role & responsibilities

• 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.