Senior AI Backend Engineer

Job description

Version 1 has celebrated 30 years in business and continues to be trusted by global brands to deliver technology and transformation solutions that drive customer success. Our deep expertise enables our customers to navigate the rapidly evolving technology landscape. We foster strong partnerships with global technology leaders including Microsoft, AWS, Oracle, Red Hat, OutSystems, Snowflake, ensuring that our customers are provided with the highest quality solutions and services. We’re an award-winning employer reflecting how our employees are at the very heart of what we do: UK & Ireland's premier AWS, Microsoft & Oracle partner 3300+ strong, €350/£300m revenue business 10+ years as a Great Place to Work in Ireland & UK Best Workplace for Women in the UK & Ireland by GPTW Best Workplace for Wellbeing in the UK by GPTW We’re a core values driven company, we hire people who share our values, and we reward those who display and foster them, it’s deeply embedded within our DNA. Invest in us and we’ll invest in you. 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 good 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 Mandatory Technical Skills Programming & Engineering • Python • REST API design and development • CI/CD pipelines • Automated testing • Distributed systems fundamentals • Relational database design (e.g. PostgreSQL) CI/CD & Infrastructure • Kubernetes • Terraform • Docker • Jenkins experience is a plus AI Familiarity • Working familiarity with Generative AI / LLM concepts: RAG, embeddings, prompt engineering, function calling • Experience integrating applications with LLM or AI platform APIs (e.g. AWS Bedrock or equivalent); deep agentic architecture or model training experience is not required • Comfortable reasoning about prompt behavior and AI output quality from an application/product perspective Cloud Platforms • Working experience with AWS (or equivalent cloud platform) • Exposure to core AWS services such as Lambda, API Gateway, S3, and CloudWatch is a plus Data Platforms • Databricks experience is a plus Production & Operations • Observability (logs, metrics, tracing, alerts) • Monitoring and reliability engineering • Performance tuning and cost optimization Security • Experience implementing AuthN/AuthZ (OAuth2/OIDC, SSO), RBAC, and secrets management in production applications Soft Skills • Strong communication skills; comfortable presenting technical recommendations directly to engineering and business stakeholders Nice to Haves Domain • Experience working within the financial services domain is preferred • Prior experience across Capital Markets, Digital Assets/Crypto, or AI infrastructure is highly desirable • Awareness of the regulatory and compliance landscape relevant to financial services technology delivery AI & Product • Experience building applications on top of LLM/agentic AI platforms (e.g. AWS Bedrock, SageMaker, or equivalent) • Familiarity with vector databases and embeddings (e.g. pgvector) for AI-powered search/retrieval features • Ability to evaluate AI feature quality from a product/UX lens (accuracy, latency, hallucination handling, graceful degradation), distinct from model-level evaluation owned by the AI Platform team Why Version 1? At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their wellbeing, professional growth, and financial stability. Share in our success with our Quarterly Performance-Related Profit Share Scheme, where employees collectively benefit from a share of our company's profits Strong Career Progression & mentorship coaching through our Strength in Balance & Leadership schemes with a dedicated quarterly Pathways Career Development programme Flexible/remote working, Version 1 is tremendously understanding of life events and people’s individual circumstances and offer flexibility to help achieve a healthy work life balance Financial Wellbeing initiatives including; Pension, Private Healthcare Cover, Life Assurance, Financial advice and an Employee Discount scheme Employee Wellbeing schemes including Gym Discounts, Bike to Work, Fitness classes, Mindfulness Workshops, Employee Assistance Programme and much more. Generous holiday allowance, enhanced maternity/paternity leave, marriage/civil partnership leave and special leave policies Educational assistance, incentivised certifications, and accreditations, including AWS, Microsoft, Oracle, and Red Hat Reward schemes including Version 1’s Annual Excellence Aw