Principal Software Engineer

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.

Experience
7-11 yrs