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Spendesk is looking for a Backend Software Engineer (IC3) to join our AI & Data Products squad and help build the next generation of product features powered by AI, ML, and intelligent automation. This is a hands-on backend role focused on turning predictive models, LLM capabilities, and business intelligence into real product experiences. You will work on backend services, APIs and MCPs that bring automation, prediction, and assisted decision-making into Spendesk’s user journeys, helping reduce manual work and make our product more proactive and intelligent.
Job Responsibility
Design, build, and operate backend services and APIs that power AI-driven, ML-driven, or automation-heavy product capabilities
Translate predictive logic and AI outputs into reliable backend behaviors that can be consumed by user-facing product flows
Build the service layer that allows intelligent features to be integrated into real workflows with strong standards on latency, reliability, and security
Ensure features are designed for production, not just experimentation, with clear ownership of deployment, monitoring, and maintainability
Partner closely with the squad’s ML Engineers to productionize predictive models and LLM-driven capabilities
Integrate model-serving APIs or LLM calls into robust backend services (your squad, or the applicative squad’s services) with proper retries, fallbacks, and observability
Help define evaluation and monitoring patterns that make intelligent product behaviors measurable over time
Contribute to the engineering patterns that allow ML and AI capabilities to be reused across multiple product features
Build backend capabilities that help automate repetitive tasks, anticipate user needs, or simplify complex workflows
Work on product experiences where AI or ML can reduce manual effort, improve decision quality, or shorten time to value for users
Partner with Product and Design to turn ambiguous ideas into concrete backend implementations with measurable impact
Bring pragmatism to delivery, balancing experimentation speed with long-term maintainability and trust
Instrument services with logs, tracing, and metrics to support production visibility and continuous improvement
Define and uphold standards around latency, resilience, failure handling, and cost efficiency for AI-powered services
Build with responsible data handling, security, and privacy by default, especially when features interact with sensitive financial workflows
Embrace a “you build it, you run it” mindset, owning the health and quality of what you ship
Work hand-in-hand with ML Engineers, Product Managers, and Designers to deliver AI-powered product capabilities end-to-end
Collaborate with applicative squads (or join them for a quarter) to integrate AI and ML services into existing user journeys and backend systems
Help define the technical interfaces and integration patterns that make intelligent services easier to adopt across the product
Share best practices in backend reliability, production readiness, and AI feature delivery across the engineering organization
Requirements
Significant experience on backend software engineering experience in production environments
A strong track record of designing and shipping reliable backend services with measurable user or business impact
Experience contributing to complex product initiatives in fast-paced, cross-functional teams
Exposure to ML-enabled or AI-enabled product features is a strong plus
Strong backend engineering skills with TypeScript / Node.js or adjacent technologies
Experience designing APIs and service layers for complex product workflows
Good understanding of distributed systems, async processing, and operational reliability
Practical experience, or strong interest, in integrating predictive models, LLM APIs, or other AI capabilities into product backends
Familiarity with technologies such as Kafka, SQS, Step Functions, PostgreSQL, and modern observability practices
Highly autonomous and comfortable owning backend systems from design to production
Product-minded, customer-focused, and motivated by building features that create visible value for end users
Comfortable working closely with ML Engineers and translating their outputs into durable product capabilities
Pragmatic and impact-driven, able to move from experimentation to production without losing engineering rigor
Fluent in written and spoken English, our business language
Nice to have
Experience productionizing ML-backed features such as classification, recommendation, forecasting, or automation
Experience integrating LLM-backed capabilities into product workflows
Familiarity with evaluation patterns for AI-powered features
Experience in SaaS, fintech, or regulated environments
What we offer
Flexible on-site and remote policy
Latest Apple equipment — the tools you need to excel
Access to Moka.care — for emotional and mental health wellbeing
Great office snacks — to fuel your day
A positive team to work with daily
Location-specific benefits including health insurance, wellness allowances, commuter support, meal vouchers, and gym memberships