Backend AI Engineer
Uplers
About the role
Experience
4.00 + years
Salary
Confidential (based on experience)
Shift
(GMT+05:30) Asia/Kolkata (IST)
Opportunity Type
Remote
Placement Type
Full time Permanent Position
Note
(*Note: This is a requirement for one of Uplers' client - Rattle)
Must have skills required
- Python
- Node.js
- LLMs
- rag
- Generative AI
- Machine Learning
- Agents
- Vector databases
- Pinecone
- Weaviate
- embeddings
Rattle is Looking for
Job Description
Von - Product by Rattle Backend AI Engineer Rattle is building the first AI-powered Revenue Intelligence Platform, solving the most critical problem in B2B sales: 75% of companies miss their revenue forecasts because the entire revenue tech stack depends on manual seller input and CRM guesswork.
The Problem We're Solving: Every Monday morning across 500,000 companies worldwide, revenue teams gather to answer three questions: Which deals will close For how much By when This is solely based on the seller's version of reality. Hence, revenue leaders spend more time inspecting deals than executing on them.
We're targeting the $2B+ forecasting market currently dominated by solutions that customers find disappointing due to their dependence on manual data hygiene. We are at an early stage of this product with a clear path to explosive growth, leveraging our experience & network in building Rattle over the last 5 years. Join us in eliminating the manual drudgery of revenue operations and building the future where forecasting is automatic, accurate, and actionable. Backed by Tier-A investors, including Lightspeed, Insight Partners, Google Ventures, and Sequoia.
What You'll Get To Do
- Own the AI/ML backend powering Von — Rattle's revenue intelligence engine — from data ingestion to model serving
- Design and build scalable APIs and services that process millions of CRM signals in real time to generate forecasting intelligence
- Work closely with the ML team to take models from experimentation to production, ensuring reliability and low-latency inference
- Build robust data pipelines that pull from Salesforce, Gong, email, calendar, and other revenue signals to feed our AI layer
- Contribute to architectural decisions on how we evolve our backend to handle enterprise-scale data volumes Work in a small cross-functional team, collaborating on feasibility, system design, and rapid prototyping
This role is tailor-made for you if
- You have 5+ years of backend engineering experience, with at least 2–3 years working on AI/ML-powered products
- You're proficient in Python and have strong experience with Node.js or TypeScript
- You've built and maintained LLM-integrated systems — whether that's RAG pipelines, prompt orchestration, or fine-tuning workflows
- You have hands-on experience with vector databases (Pinecone, Weaviate, or similar) and embedding models
- You're comfortable with REST and event-driven architectures (Kafka, SQS, or similar)
- You have strong knowledge of relational and non-relational databases You thrive in early-stage startup environments and get excited about 0
- 1 product building You make pragmatic decisions fast — you know when to build vs. buy and when good enough ships better than perfect
We already like you if
- You've shipped a production AI feature end-to-end — not just experiments in notebooks
- You've worked with CRM or GTM data before (Salesforce, HubSpot, Gong, etc.)
- You love TechCrunch. We are obsessed with reading and talking about startups
- You've contributed to open-source AI/ML tooling or have a side project in this space
More reasons to join us
- Shape the AI roadmap: You'll have a direct hand in defining how intelligence gets built into our product
- Have meaningful impact: Your work will power forecasting decisions for thousands of enterprise revenue teams
- Flexibility: You get to design your workday around your life — we believe in outcomes and not counting hours
- Listen and be heard: We love feedback, we enjoy receiving and giving each other feedback, and we grow together
How to apply for this opportunity
- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
About Uplers
Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.
(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).
So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!
Requirements
- 5+ years of backend engineering experience
- 2–3 years working on AI/ML‑powered products
- Proficient in Python and strong experience with Node.js or TypeScript
- Built and maintained LLM‑integrated systems (RAG pipelines, prompt orchestration, fine‑tuning workflows)
- Hands‑on experience with vector databases (Pinecone, Weaviate, or similar) and embedding models
- Comfortable with REST and event‑driven architectures (Kafka, SQS, or similar)
- Strong knowledge of relational and non‑relational databases
- Experience shipping production AI features end‑to‑end
- Familiarity with CRM or GTM data sources (Salesforce, HubSpot, Gong, etc.)
Responsibilities
- Own the AI/ML backend powering Von — Rattle's revenue intelligence engine — from data ingestion to model serving
- Design and build scalable APIs and services that process millions of CRM signals in real time to generate forecasting intelligence
- Work closely with the ML team to take models from experimentation to production, ensuring reliability and low‑latency inference
- Build robust data pipelines that pull from Salesforce, Gong, email, calendar, and other revenue signals to feed the AI layer
- Contribute to architectural decisions on how to evolve the backend to handle enterprise‑scale data volumes
- Collaborate in a small cross‑functional team on feasibility, system design, and rapid prototyping
Benefits
Skills
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