Senior Backend Engineer / Member of Technical Staff

Company Overview Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become one of the fastest growing enterprise AI platforms worldwide and recently closed a $75 million Series A, one of the largest fintech Series A rounds ever. The round was backed by FT Partners, Y Combinator, LocalGlobe, QED, 13books, and other top global investors, bringing total funding to $90 million. Job Description As a Senior Backend Engineer at Model ML, you'll be at the forefront of building and scaling the infrastructure that powers our our product. You'll design and implement robust, high-performance backend systems that handle complex data pipelines, enable seamless AI model deployment, and ensure enterprise-grade security and compliance for our financial services clients. Working closely with machine learning engineers, product teams, and infrastructure specialists, you'll architect scalable solutions that process sensitive financial data with precision and reliability. This role offers the opportunity to tackle unique technical challenges at the intersection of AI and finance, where your work will directly impact how financial institutions leverage artificial intelligence to transform their operations. You'll drive technical decisions, mentor junior engineers, and help shape the engineering culture as we scale our platform to serve the world's leading financial organisations. Responsibilities Design, develop, and maintain scalable backend services and APIs that power Model ML's AI workspace platformBuild and optimize data pipelines for processing large-scale financial datasets with high accuracy and performanceImplement robust security measures and ensure compliance with financial industry regulations (SOC 2, GDPR, FCA requirements)Collaborate with ML engineers to productionize machine learning models and integrate them into backend systemsOptimize database schemas and queries for high-throughput, low-latency operations across distributed systemsLead technical design reviews and mentor junior and mid-level engineersMonitor system performance, troubleshoot production issues, and implement solutions to improve reliability and uptimeContribute to engineering best practices, code quality standards, and technical documentation What You Can Expect It won't be easy; in fact, it will be very hard.BUT, it will be a lot of fun.You need to be comfortable with being uncomfortable; timelines will change, priorities will most likely shift. Requirements 7+ years of professional backend engineering experience with a proven track record of building and scaling production systemsExpert-level proficiency in Python and modern web frameworks, particularly FastAPI (or similar frameworks like Flask or Django)Deep understanding of relational databases, especially PostgreSQL—including query optimisation, indexing strategies, and performance tuningProven experience scaling databasesStrong knowledge of caching strategies and in-memory data stores, particularly RedisHands-on experience with asynchronous task processing using Celery or equivalent distributed task queuesProficiency with message brokers and event-driven architectures (Azure Service Bus, RabbitMQ, Kafka, or similar)Solid understanding of RESTful API design principles and microservices architecture patternsExperience with cloud platforms (Azure preferred; AWS or GCP acceptable) and containerization technologies (Docker, Kubernetes)Strong knowledge of security best practices, authentication/authorization mechanisms, and data encryptionFamiliarity with CI/CD pipelines, automated testing, and version control systems (Git)Excellent problem-solving skills with the ability to debug complex distributed systemsStrong communication skills and experience collaborating with cross-functional teamsBachelor's degree in Computer Science, Engineering, or equivalent practical experience What We Offer Competitive salary + equityPerformance-based incentivesOpportunity to be instrumental in our expansion into the marketSupportive and innovative work environment About The Interview Our Process: We're very conscious of everyone's time, so we want to make the process as efficient as possible. Call 1: 30-minute intro call with our Talent Acquisition team Call 2: 30-minute technical screen Call 3: 20-minute systems design deep-dive Call 4: Onsite interview with Engineering Leadership