About the role
Requirements:
- 7+ years of professional software development experience, with substantial depth in backend and distributed systems engineering.
- Expert-level proficiency in at least one modern programming language (Python, Java, C#, Go, or similar); demonstrable ability to work across languages and adapt rapidly to new technology contexts.
- Expert-level knowledge of relational and NoSQL data stores (PostgreSQL, MySQL, MongoDB, Redis); experience with query optimization, schema design for high-throughput systems, and data migration strategies.
- Proven experience designing and governing RESTful and event-driven APIs at platform scale; experience with API versioning, backward compatibility, and deprecation strategies.
- Deep understanding of cloud-native architecture on at least one major cloud provider (AWS, Azure, or GCP); experience with multi-region, high-availability, and cost-optimized designs.
- Hands-on experience owning and evolving CI/CD platforms, deployment strategies (blue/green, canary, feature flags), and production observability (tracing, metrics, alerting).
- Strong experience with containerization and container orchestration (Docker, Kubernetes) in production environments.
- Deep expertise in distributed systems design, consistency models, fault tolerance, event-driven architecture, microservices, and service mesh patterns.
- Demonstrated record of leading end-to-end delivery of complex, high-impact technical initiatives from ambiguous requirements through production at scale.
- Demonstrated performance engineering expertise in profiling, load testing, capacity planning, and tuning at scale.
- Security engineering depth: threat modelling, secure design reviews, knowledge of relevant vulnerability classes, and experience with regulated/compliant systems.
- Proven ability to mentor engineers effectively and grow technical capability within a team.
- Experience with payment processing systems, financial transactions, or financial services domain; solid understanding of transaction lifecycle, settlement, reconciliation, and compliance requirements.
- Working knowledge of PCI-DSS and relevant payment industry security standards; experience ensuring platform compliance.
- Strong ability to integrate AI/ML capabilities into production systems; able to define standards and evaluate AI components for production readiness, safety, and risk in a payments context.
Good to have skills:
- Experience with foreign exchange systems, capital markets infrastructure, or complex financial instrument processing.
- Hands-on experience building, deploying, and operating ML models (fraud detection, risk scoring, and anomaly detection) in production payment environments.
- Experience with LLM integration patterns, prompt engineering, RAG architectures, or AI agent frameworks at a production scale.
- Advanced knowledge of message streaming and event sourcing patterns (Kafka, Flink, and event-driven architecture at scale).
- Contributions to open-source projects, technical publications, or conference presentations.
- Experience in a formal technical lead or staff engineer capacity.