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Senior AI Engineer LLM & Generative AI

Senior AI Engineer LLM & Generative AI

UFS Networks

4 - 8 years

14 - 18 Lacs

hubli mangaluru mysuru bengaluru belgaum

Posted:1 day ago| Platform:

Apply

Skills Required

computer science backend github front end orchestration cloud security gcp data processing monitoring python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Senior AI Engineer - LLM & Generative AI

We are seeking a

Senior AI Engineer

with practical experience in

LLMs, LangChain or similar frameworks, and Retrieval- mented Generation (RAG)

systems. In this role, you will help design and deploy intelligent, secure, and scalable AI solutions that enhance Zscaler s products and internal automation tools.

The position emphasizes

AI backend development and orchestration using Python

cloud

deployment (AWS preferred, GCP optional)

, and

integration of LLM-based services

with light

front-end development

for chat interfaces, copilots, and dashboards.

Responsibilities

AI Solution Development:

Build and maintain production-grade AI systems using

LLMs, LangChain, and RAG pipelines

to solve enterprise-scale problems.

Model Integration:

Implement, fine-tune, and evaluate LLMs using frameworks such as

LangChain, LlamaIndex, Hugging Face, or OpenAI API

Backend & API Engineering:

Develop scalable

Python microservices

and APIs for inference and knowledge retrieval.

Deploy and operate services on

AWS (preferred)

GCP

using

EKS

ECS

, or

Cloud Run

Implement observability, itoring, and autoscaling for production workloads.

Retrieval- mented Generation (RAG):

Design and optimize retrieval workflows using vector databases like

FAISS

Pinecone

, or

Milvus

Integrate both structured and unstructured data into LLM pipelines for grounded responses.

Front-End Integration:

Collaborate with UI teams to integrate AI experiences into dashboards or chat UIs using

React

Next.js

, or

TypeScript

. Ensure seamless communication between front-end components and AI APIs.

Cloud & DevOps:

Containerize and deploy using

Docker

and

Kubernetes

Implement

CI/CD pipelines

with tools like Jenkins, Gi b Actions, or Terraform.

Cross-Functional Collaboration:

Work closely with product, data science, and platform teams to deliver robust, secure, and impactful AI services.

Continuous In ation:

Stay current with LLM, RAG, and multi-agent system advancements and drive their adoption across products.

Qualifications

Must-Have

Solid working experience with

Python

for AI service development, API integration, and data processing.

Practical hands-on experience with

LangChain

RAG pipelines

, or similar developer frameworks.

Familiarity with

LLM integration

prompt design

, and

embedding-based retrieval

Experience deploying applications on

AWS (preferred)

GCP

, particularly with

EKS

ECS

, or

Cloud Run

Proficiency with

Docker

Kubernetes

, and cloud-native service orchestration.

Experience building

RESTful or GraphQL APIs

for AI and data services.

Understanding of

cloud security

scalability

, and

performance optimization

principles.

Good-to-Have

Experience developing conver ional UIs, copilots, or AI-enabled dashboards (e.g., Slack apps, chat widgets).

Familiarity with

React

Next.js

, or

TypeScript

for front-end feature integration.

Exposure to

Hugging Face Transformers

LlamaIndex

, or

LangGraph

ecosystems.

Knowledge of

vector databases

and

data pipeline management

. Understanding of

compliance, privacy, and responsible AI practices

in enterprise environments.

Education & Experience

Bachelor s or Master s degree in Computer Science, Engineering, or a related field.

Typically

4-8 years of experience

in software or AI engineering, including

2+ years of hands-on experience with LLMs, LangChain, or RAG systems

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Senior AI Engineer LLM & Generative AI

Experience & Salary

Skills Required

Work Mode

Job Type

Job Description

Senior AI Engineer - LLM & Generative AI

Senior AI Engineer

LLMs, LangChain or similar frameworks, and Retrieval- mented Generation (RAG)

AI backend development and orchestration using Python

cloud

deployment (AWS preferred, GCP optional)

integration of LLM-based services

front-end development

Responsibilities

AI Solution Development:

LLMs, LangChain, and RAG pipelines

Model Integration:

LangChain, LlamaIndex, Hugging Face, or OpenAI API

Backend & API Engineering:

Python microservices

AWS (preferred)

GCP

EKS

ECS

Cloud Run

Retrieval- mented Generation (RAG):

FAISS

Pinecone

Milvus

Front-End Integration:

React

Next.js

TypeScript

Cloud & DevOps:

Docker

Kubernetes

CI/CD pipelines

Cross-Functional Collaboration:

Continuous In ation:

Qualifications

Must-Have

Python

LangChain

RAG pipelines

LLM integration

prompt design

embedding-based retrieval

AWS (preferred)

GCP

EKS

ECS

Cloud Run

Docker

Kubernetes

RESTful or GraphQL APIs

cloud security

scalability

performance optimization

Good-to-Have

React

Next.js

TypeScript

Hugging Face Transformers

LlamaIndex

LangGraph

vector databases

data pipeline management

compliance, privacy, and responsible AI practices

Education & Experience

4-8 years of experience

2+ years of hands-on experience with LLMs, LangChain, or RAG systems

More Jobs at UFS Networks

Senior AI Engineer LLM & Generative AI

Mock Interview