14 Aug
|
Version 1
|
Mumbai
Job Description
About Galaxy
Galaxy is a global leader in digital assets and AI infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. Founded in 2018 and headquartered in New York City, we serve institutions, startups, protocols, and investors across a platform spanning trading, asset management, tokenization, and large-scale AI and high-performance computing data centers. This role sits on the AI products team, a small, high-ownership group that takes ideas from prototype to production and ships them at scale.
Why you'll want this role
• Greenfield, high-ownership work: build new AI products end to end, rather than maintaining legacy systems.
• Real impact: your work ships to institutional and individual clients and runs in production, not stuck in prototype.
• Modern stack: hands-on with LLMs, agentic systems, and AWS-native AI services.
Role Overview
As a Backend Engineer on our AI Products team, you will design, build, and operate the backend services that power products across Galaxy. You will work with product and engineering teams to implement features end-to-end, from data model to API to production deployment.
Many of these products integrate with Galaxy's AI Suite, our internal platform for Generative and Agentic AI, built on AWS Bedrock, AgentCore, and SageMaker. Day to day, you'll mostly be consuming that platform, calling its APIs, wiring LLM and RAG-based features into application logic, and reasoning about prompts and model behavior as part of building a positive product, rather than building or owning the platform itself. From time to time, though, you may be asked to contribute directly to the AI stack, so foundational AI knowledge is important.
Key Responsibilities
Backend Engineering
• Design, build, and maintain backend services and REST APIs that power Galaxy products
• Design data models and schemas, and work with relational and other data stores as appropriate
• Apply strong software engineering and distributed systems principles to day-to-day development
• Write automated tests and maintain CI/CD pipelines for reliable, repeatable deployments
• Diagnose and resolve production issues related to latency, reliability, and data quality
AI Integration
• Integrate backend services with Galaxy's AI Suite (Bedrock, AgentCore, SageMaker-based APIs) built and maintained by the AI Platform team
• Wire LLM, embedding, and RAG-based capabilities exposed by the AI Suite into application features
• Apply prompt engineering and function calling at the application level to build reliable AI-powered features
• Contribute to testing and quality checks for AI-driven features from a product/application perspective
Cross-Stack Contribution
• Contribute across the stack as needed, such as data pipelines, infrastructure, or frontend touchpoints, depending on team and project needs
• Partner with full stack engineers, the AI Platform team, and data teams to deliver features end-to-end
• Balance delivery speed with code quality, maintainability, and operational health
Collaboration & Growth
• Work closely with product managers and business stakeholders to translate requirements into working software
• Collaborate with the AI Platform team to stay current on AI Suite capabilities and best practices for consuming them
• Share knowledge with other engineers on backend and AI-integration best practices
📌 Senior AI Backend Engineer (Mumbai)
🏢 Version 1
📍 Mumbai