Staff Software Engineer

SPD Technology is a global software product development company specializing in fintech, digital payment solutions, data engineering, AI/ML, and Cloud technologies. Founded in 2006, it has delivered over 460 projects for clients ranging from Fortune 500 firms to startups. Key clients include PitchBook and Morningstar, with four clients generating over $4B in annual revenue each. The company has over 650 engineers across 35 countries.

• Degree in Computer Science, Information Systems, or equivalent practical experience.
• Minimum 6 years software engineering experience using Java or a comparable object-oriented language.
• At least 3 years developing microservices and cloud-based distributed or event-driven systems.
• Practical knowledge of service-oriented architecture, domain-driven design, clean architecture, hexagonal architecture, and common architecture patterns.
• Experience implementing agentic applications and evaluation-based tools.
• Experience designing RESTful APIs and event-driven applications using Kafka.
• Experience with mainstream relational databases, caching, replication, and search technologies.
• Experience with Google Cloud Platform or Amazon Web Services and container orchestration technologies such as Kubernetes.
• Strong problem-solving skills and ability to provide technical leadership across multiple teams without formal authority.
• Excellent written and verbal communication skills with engineers, managers, and product partners.

• Solve strategic engineering problems hands on, including building prototypes and reference implementations.
• Design and deliver working software encompassing backend systems and micro-frontend patterns.
• Automate architectural conformance through AI-based checks and fitness functions.
• Break down complex problems using domain-driven design and make practical decisions under ambiguity.
• Define, establish, and evaluate measurable quality goals including performance, scalability, security, and maintainability.
• Document architecture evolution including current and target states, constraints, and decisions.
• Make explicit engineering tradeoffs with balanced recommendations considering cost and operational impacts.
• Create reusable engineering patterns such as scaffolding and reference architectures.
• Guide delivery teams via architecture and design reviews and coaching.
• Communicate technical context clearly to engineers, technical leaders, product managers, and business stakeholders.