Backend Engineer - Context Layer & Platform

Client is a Seed Funded Start-up in MarTech growing rapidly in US. They are looking to hire from India and move them to US (If the candidate is comfortable) on O1 Visa

The Role

We are looking for a Founding Backend Engineer to architect the nervous system of our AI

Operator.

Our core decision engine relies on a perfect understanding of reality to make high-stakes

financial trades. Your job is to build the Context Layer which serves as the sensory system

that determines how our system sees the world.

You will own the infrastructure that fuses rigid financial data with messy and unstructured

signals. You will architect the universal data model that standardizes chaotic inputs from ad

platforms, MMPs, first-party data and our own internal actions into a rigid and queryable

schema to ensure our automated trading never misses a beat.

What You'll Do

• Standardize Data Schemas : Design and maintain the canonical data models that normalize conflicting metrics across disparate sources. You will map data from ad platforms like Meta and Google, MMPs like AppsFlyer, first-party data and our own internal actions and observers into a single unified language for our models.
• Build Deep 1P Data Integrations : Construct pipelines to ingest high-fidelity signals directly from the source. You will fetch events, conversion values, inventory logic and customer lifetime value models directly from enterprise data warehouses like Snowflake, Databricks and Redshift.
• Integrate Unstructured Data & LLMs : Build workflows that scrape and process multimodal data from ad libraries and social platforms. You will work with LLMs to structure this chaos including competitor creatives, market trends and visual signals into quantitative inputs.
• Architect the Observer Framework : Build the logging and observation infrastructure that records every state change. You ensure that every internal decision and external market shift is captured in our standardized schema to create a perfect historical record for causal analysis.

Who You Are

Bonus Points

Compensation & Benefits