Core Responsibilities :

- Design, Build & Manage Lifecycle of AI systems

- Multi-Agent Orchestration : Design and implement multi-agent workflow(s) for AI functionalities : Intent Detection, Creation of High-Quality Response, Logic Audit, Query Clarification, Auto-Visualization, Code Generation, Syntax-Validation, etc.

- Intelligence Enhancement : Build a Human-in-the-Loop (HITL) based feedback flywheel & loops to constantly improve golden data store & response accuracy.

- Semantic Layer Mastery : Construct Data Dictionary to define complex business terms. Ensure the AI speaks the language of our customers & business stakeholders, in a friendly but professional tone, that is warm & human-like & easy to understand.

- AI Lifecycle and Full-Stack AI Execution : Own major parts of the AI Roadmap. Deploy LLMs & Perform code execution via cloud services. Ensure high quality code.

- Data Governance & Observability : Ensure every AI-generated SQL/Code is analysed & evaluated before & after execution. Maintain strict data quality / sanity / reliability standards; syntax+logical correctness/consistency; & semantic accuracy.

Roles Requirements :

The Intersection of Data Rigor and AI/GenAI Innovation We are looking for a world-class AI specialist who is part Cloud AI Practitioner, part Data Science (DS) innovator, and part MLOps ninja. Essentially, a fullstack AI expert.

[MH] Must-Have Skills & Experience :

- AI/ML Core : 2+ years of experience with Python, AI libraries, GIT, GitHub, production grade AI/ML models & systems. 2+ years developing innovative AI & DS features.

- GenAI & RAG : Experience building high quality Retrieval-Augmented Generation (RAG) architectures, Knowledge-Bases (KBs), & AI-Agents, using LLMs.

- Data Engineering (DE) : Deep proficiency in SQL and PostgreSQL, and vector databases for semantic search. Experience with vector embeddings and ETL.

- Cloud AI Practitioner : Hands-on experience with AWS Bedrock, Lambda, RDS, Sagemaker, AI-Agent frameworks and other AI Services in AWS/GCP/Azure.

- AI Tooling Expertise : Expert-level usage of Cursor, Claude Code, Gemini, or Replit to automate design, code generation, debugging, testing and deployment.

[SH] Should-Have Skills & Experience :

- Conversational BI : Experience building AI Assistants providing instant customized insights in response to natural language queries, using LLMs like Claude or GPT.

- Orchestration Frameworks : Experience with AgentCore, LangGraph, N8N, or CrewAI, for multi agent pipelines/workflows. Exp with Linux & open-source tools.

- Financial/Fintech/AI Rigor : Can handle complex financial metrics & ensure data sanity & quality. Ability to understand/improve model quality & monitor for model drift.

- MLOps & AI Governance : CI/CD for LLMs, LLMOps, Prompt Versioning, AI/ML Models Selection/Training/Fine-Tuning/Testing/Monitoring, Robust SCM practices, Agile/Scrum, AI Reliability, Security, AI Performance & Cost Optimization, etc.

[GTH] Good-To-Have Skills & Experience :

- Educational Background : Degree in Computer Science or Engineering or Data Science or AI/ML from a premier institution (IITs/NITs/BITS/IIIT) or a top university.

- Frontend & Backend Experience : Vibe-coding Experience, Visualizations (using Charts.js, D3.js, etc.), Streamlit, FastAPI (APIs), etc., to complete AI Assistant POCs.

- Prototyping Speed : Ability to build prototypes of AI features and AI/ML/GenAI POCs (using AI Agents & AI tools) fast, give good demos, & iterate fast to improve quality.