Rag Backend Engineer – Ai/ml Systems

Year    MH, IN, India

Job Description

Company Description:



Onelab Ventures

is a leading technology company that specializes in

custom AI agent solutions

and

software development

. We collaborate with startups and enterprises to transform innovative ideas into

scalable, intelligent systems

that drive growth and efficiency.

Our team of

AI specialists, developers, designers, and product managers

has delivered over

100+ successful projects

, impacting

~1 million weekly active users

across sectors including

SaaS, Fintech, and Healthcare

. Leveraging

agile methodologies

and advanced

AI frameworks

, we ensure every product is

reliable, efficient, and user-centric

.

Role Description:



This is a

full-time, on-site role

based in

Pune

.

We are seeking a highly skilled

Backend RAG (Retrieval-Augmented Generation) Engineer

to

design

,

develop

, and

maintain RAG-based systems

powering intelligent enterprise solutions. You will work within an existing framework, take ownership of core modules, and integrate AI with real-world business tools like

CRMs, HubSpot, and internal systems

.

This role involves

deploying Model Context Protocol (MCP) servers

, working within an

event-driven

,

horizontally scalable architecture

, and balancing

rapid prototyping

with

production-ready engineering

.

Key Responsibilities:



Build and maintain

Retrieval-Augmented Generation (RAG)

pipelines Take ownership of key modules within a

custom RAG framework

Deploy and manage

MCP (Model Context Protocol) servers

Integrate AI with

enterprise tools

like

HubSpot

,

CRMs

,

email systems

, and

internal APIs

Work with

event-driven

,

horizontally scalable

backend architectures Rapidly

prototype

while ensuring

clean, maintainable, production-grade code

Contribute to evolving

system design

and

data architecture


Technical Skills Required:

Primary Must-Haves:



Hands-on experience with LlamaIndex

(preferred over LangChain) for RAG pipeline development

Built or maintained RAG systems

integrating

10-12+ heterogeneous data sources

Familiar with

automation

and building

AI-driven workflows

that generate actionable insights

Integration experience

with

CRM systems

(e.g.,

HubSpot

),

email platforms

, and

enterprise APIs

Strong foundation in

scalable backend development

and

cloud deployment

(AWS/GCP)

Bonus/Nice to Have:



Experience working with

event-driven architectures

Familiarity with

microservices

,

Docker

,

Kubernetes

,

Redis

Exposure to

AI product engineering

,

LLM fine-tuning

, or

custom AI agents


Work Details:



Location: On-site -

Pune Office


Type: Full-Time
Join Date: Immediate joiners preferred

Experience 1-4 year

Job Type: Full-time

Pay: ?590,000.00 - ?800,000.00 per year

Benefits:

Health insurance Provident Fund Work from home
Ability to commute/relocate:

Hinjewadi, Pune, Maharashtra: Reliably commute or planning to relocate before starting work (Preferred)
Application Question(s):

Have you built a RAG pipeline using Llama Index? Please describe briefly. How many types of data sources have you integrated into a single RAG system? Have you deployed Model Context Protocol (MCP) servers in production? What CRMs or business tools have you connected with your backend systems? Do you have experience working with event-driven or horizontally scalable backend architectures? Which cloud platforms and deployment tools are you most comfortable with? Are you available to attend the final in-person interview at our Pune office? What your Current CTC? What your expected CTC? What your notice period?
Experience:

RAG: 2 years (Preferred) LlamaIndex: 2 years (Preferred) Model Context Protocol: 2 years (Preferred)
Work Location: In person

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Job Detail

  • Job Id
    JD3869887
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    MH, IN, India
  • Education
    Not mentioned
  • Experience
    Year