AI Engineer

AU SMALL FINANCE BANK; Navi Mumbai; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

AU SMALL FINANCE BANK in Navi Mumbai is seeking a hands-on MLOps/AI Engineer to help build scalable multimodal LLM-based agents and AI systems. You will leverage Python, PyTorch, LangChain, and cloud platforms to deploy, monitor, and improve models in production.

The role emphasizes RAG, semantic search, dataset development, and collaboration with data scientists. You will implement governance for models and data, ensure reproducible experiments, and ship reliable ML tooling in a fast-paced

Qualifications

• Bachelor's degree in computer science, Software Engineering, or related field.
• 2-5 years of experience in MLOps, DevOps, or related roles.
• Strong programming experience in Python-based deep learning frameworks (PyTorch, JAX, TensorFlow).
• Familiarity with ML concepts and cloud platforms (AWS/Azure/GCP) and IaC tools like Terraform.

Responsibilities

• Agentic AI Development: Build scalable multi-modal LLM-based AI agents using LangGraph, Autogen, or Crewai.
• AI Research: Develop solutions for RAG, semantic search, knowledge representation, and NLP.
• Technical Expertise: Work with Python, LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure.
• LLM & NLP: Hands-on experience with LLMs, NLP, and applying ML to real problems.
• Dataset Development: Create datasets for training/evaluating ML models.
• Customer Focus: Deliver value by deeply understanding user problems.
• Adaptability: Thrive in a fast-paced early-stage venture.
• Model Deployment & Management: Automate deployment, monitoring, and retraining.
• Collaboration & Optimization: Review and optimize ML code with data scientists.
• Version Control & Governance: Implement governance for models and data.

Skills

Python

LlamaIndex/LangChain

PyTorch

HuggingFace

FastAPI

Postgres

SQLAlchemy

Alembic

OpenAI

Docker

Azure

TypeScript

React

Education

Bachelor's degree in computer science or related field

Tools

Terraform

Apache Airflow

Prefect

Job description

• Agentic AI Development : Work on building scalable multi-modal Large Language Model (LLM) based AI agents, leveraging frameworks such as LangGraph, Microsoft Autogen, or Crewai.
• AI Research and Innovation : Research and build innovative solutions to relevant AI problems, including Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, tool usage, fine-tuning, and reasoning in LLMs.
• Technical Expertise : Proficiency in a technology stack that includes Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, and React.
• LLM and NLP Experience : Hands-on experience working with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems.
• Dataset Development : Strong track record of building datasets for training and/or evaluating machine learning models.
• Customer Focus : Enjoy diving deep into the domain, understanding the problem, and focusing on delivering value to the customer.
• Adaptability : Thrive in a fast-paced environment and are excited about joining an early-stage venture.
• Model Deployment and Management : Automate model deployment, monitoring, and retraining processes.
• Collaboration and Optimization : Collaborate with data scientists to review, refactor, and optimize machine learning code.
• Version Control and Governance : Implement version control and governance for models and data.

Job Description

Key Responsibilities

• Agentic AI Development : Work on building scalable multi-modal Large Language Model (LLM) based AI agents, leveraging frameworks such as LangGraph, Microsoft Autogen, or Crewai.
• AI Research and Innovation : Research and build innovative solutions to relevant AI problems, including Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, tool usage, fine-tuning, and reasoning in LLMs.
• Technical Expertise : Proficiency in a technology stack that includes Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, and React.
• LLM and NLP Experience : Hands-on experience working with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems.
• Dataset Development : Strong track record of building datasets for training and/or evaluating machine learning models.
• Customer Focus : Enjoy diving deep into the domain, understanding the problem, and focusing on delivering value to the customer.
• Adaptability : Thrive in a fast-paced environment and are excited about joining an early-stage venture.
• Model Deployment and Management : Automate model deployment, monitoring, and retraining processes.
• Collaboration and Optimization : Collaborate with data scientists to review, refactor, and optimize machine learning code.
• Version Control and Governance : Implement version control and governance for models and data.

Required Qualifications

• Bachelor's degree in computer science, Software Engineering, or a related field
• 2-5 years of experience in MLOps, DevOps, or related roles
• Have strong programming experience and familiarity with Python based deep learning frameworks like Pytorch, JAX, Tensorflow
• Have strong familiarity and knowledge of machine learning concepts
• Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform

Desired Skills

• Experience with experiment tracking and model versioning tools
• You have experience with technology stack: Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React.
• Knowledge of data pipeline orchestration tools like Apache Airflow or Prefect
• Familiarity with software testing and test automation practices
• Understanding of ethical considerations in machine learning deployments
• Strong problem-solving skills and ability to work in a fast-paced environment