AI Engineer (Backend) - Assistant Manager

Deloitte Shared Services India; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Deloitte Shared Services India is seeking an experienced AI Backend Engineer to design, build, and deploy high-scale AI services in Bengaluru. You will focus on LLM workflows, Agentic AI, and robust backend systems powering our AI platform.

You will collaborate with data scientists, ML engineers, and frontend teams, delivering production-grade APIs with Python, FastAPI/Flask/Django, and containerized deployments on Azure/AWS/GCP.

Qualifications

• 3-6 years of backend development experience, with at least 2+ years in AI/ML applications.
• Proficient in Python with FastAPI/Flask/Django experience.
• Experience integrating LLMs and AI workflows.
• Knowledge of vector databases (Chroma, FAISS, Qdrant) and SQL/NoSQL.
• Experience deploying with Docker/Kubernetes and cloud services (Azure/AWS/GCP).
• Strong understanding of distributed systems and REST APIs.
• Bachelor's or Master's in CS/AI.

Responsibilities

• AI Integration & Development: Design and implement APIs for AI/ML model inference, focusing on LLM workflows, NLP, and Agentic AI systems.
• Backend Architecture: Build and maintain scalable, asynchronous distributed systems and microservices using Python/FastAPI/Flask/Django.
• Data Pipeline Management: Develop ETL/ELT pipelines and manage data processing to train, fine-tune, and serve models.
• Production Deployment: Deploy AI models into production environments using Docker, Kubernetes and cloud services (Azure/AWS/GCP).
• Performance Optimization: Optimize backend services for high performance, low latency, and scalability.
• Collaboration & Mentorship: Work with full-stack devs, data scientists, ML engineers, and front-end teams to integrate AI capabilities and mentor juniors.

Skills

Python

Python frameworks

AI/ML apps

LangChain

LlamaIndex

HuggingFace

PyTorch

Chroma

FAISS

Qdrant

PostgreSQL

MySQL

MongoDB

Redis

Elasticsearch

Azure

AWS

GCP

CI/CD

MLOps

REST APIs

Distributed systems

Async processing

System design

Education

Bachelor's or Master's in CS/AI

Tools

Docker

Kubernetes

Azure

AWS

GCP

FastAPI

Flask

Django

SQL

MongoDB

Redis

Job description

The team:

Enterprise technology has to do much more than keep the wheels turning; it is the engine that drives functional excellence and the enabler of innovation and long-term growth. Learn more about ET&P

Your work profile

We are seeking a highly skilled AI Backend Engineer to design, build, and deploy high-scale, production-grade AI services. As a key member of our engineering team, you will focus on integrating Large Language Models (LLMs), Agentic AI, optimizing RAG (Retrieval-Augmented Generation) pipelines, and architecting robust backend systems that power our core AI platform.

Job Responsibilities:

• AI Integration & Development: Design and implement APIs for AI/ML model inference, specifically focusing on LLM workflows, NLP, and Agentic AI systems.
• Backend Architecture: Build and maintain scalable, asynchronous distributed systems and microservices using Python/FastAPI/Flask/Django.
• Data Pipeline Management: Develop robust ETL/ELT pipelines and manage data processing to train, fine-tune, and serve models.
• Production Deployment: Deploy AI models into production environments utilizing containerization (Docker, Kubernetes) and cloud services (Azure/AWS/GCP).
• Performance Optimization: Optimize backend services for high performance, low latency, and maximum scalability.
• Collaboration & Mentorship: Work closely with full-stack developers, data scientists, ML engineers, and front-end teams to integrate AI capabilities into end-user products, providing technical leadership and mentoring junior developers.

Key skills required:

• Experience: 3-6 years of professional backend development experience, with at least 2+ years specialized in AI/ML applications.
• Languages: Expert-level proficiency in Python (FastAPI, Flask, Django).
• AI Frameworks: Hands-on experience with LLM frameworks like LangChain, LlamaIndex, Hugging Face, or PyTorch/TensorFlow.
• Database Systems: Proficient in Chroma, FAISS, Qdrant (Vector DB), SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, Elasticsearch) databases.
• Cloud & DevOps: Proven experience with Azure, AWS (S3, EC2, Lambda) or GCP, and CI/CD pipelines, MLOps.
• Architecture: Strong knowledge of distributed systems, async processing, RESTful APIs, and system design patterns.
• Education: Bachelors or Master’s degree in Computer Science, AI, or related fields.