• Join a collaborative team of Engineers to develop, release, and maintain the Achievers Platform and supporting services for user lifecycle management and HRIS integrations • The tech stack: Python, Go, PHP, React, Kubernetes, Docker, Pub/Sub, GraphQL, microservices and more • Work independently on complex tasks, designing small to mid-size components for user data management and HRIS integration systems • Develop scalable solutions that improve system performance and handle large-scale user lifecycle events • Troubleshoot issues across the full stack, from API integrations to database performance • Actively review peers' code for quality, maintainability, and alignment with architectural standards • Estimate effort for mid-to-large initiatives and contribute meaningfully to sprint planning and technical discussions • Begin mentoring junior engineers, sharing knowledge and fostering collaborative growth • Stay up to date on emerging technologies and corporate engineering guidelines, best practices, processes and tools • Ensure that systems, designs, and decisions are well-documented, making it easier for other engineers to understand, maintain, and expand upon your work

• Design, develop, and maintain features using TypeScript and React, building responsive, accessible, and performant user interfaces. • Modification of database objects using SQL (stored procedures, views, tables etc.). • Act as a technical advisor and thought leader, guiding high-impact initiatives across the domain. • Lead architectural discussions and contribute to system design decisions with a focus on maintainability, scalability, and performance. • Solve highly complex technical problems using advanced knowledge and broad experience. • Write and maintain automated unit, integration, and UI tests to improve quality and reduce defects. • Drive improvements in engineering practices, standards, and methodologies • Refactor and optimize systems to improve efficiency, maintainability, and performance. • Ensure adherence to security, compliance, and reliability standards. • Establish credibility and influence across teams by clearly communicating complex technical concepts. • Partner with product, architecture, and business stakeholders to deliver impactful solutions. • Build strong cross-functional relationships and contribute to broader organizational initiatives. • Translate technical concepts into business value for non-technical stakeholders. • Mentor engineers by sharing expertise, guiding design decisions, and helping avoid technical pitfalls. • Actively elevate team capabilities through coaching and knowledge sharing. • Foster a culture of continuous learning and improvement. • Leverage AI-assisted development tools (e.g., code generation, testing support, documentation automation) to increase productivity and accelerate delivery cycles • Identify opportunities to integrate AI into products, engineering workflows, and operational processes. • Use AI responsibly to enhance—not replace—engineering judgment, ensuring quality, security, and ethical standards. • Continuously evaluate and adopt emerging tools and technologies to improve team efficiency and effectiveness.

• Develop and maintain systems using sound architectural principles, ensuring high availability, resource efficiency, and self-healing capabilities. • Lead the design and development of scalable API integrations, ensuring seamless connectivity and adaptability with external data streams and partners. • Design comprehensive logging, tracking, and alerting systems to monitor crucial system health metrics, ingestion quality, and customer behavior for proactive risk resolution. • Enhance CI/CD pipelines, support automated testing strategies, and establish rigorous coding standards to ensure safe, secure, and frequent production deployments. • Actively participate in Agile planning, conduct thorough architecture reviews, and produce clean technical documentation to support developer onboarding and peer mentorship. • Evaluate and integrate emerging technologies, including AI-assisted development tools and automation frameworks, to optimize code creation, reduce technical debt, and solve complex business problems.

• Design, develop, test, deploy, and maintain scalable software solutions supporting the Whitespace Answers Platform and Iris AI ecosystem. • Build backend services, APIs, data pipelines, and analytic applications using modern software engineering practices. • Write clean, efficient, maintainable, and testable code primarily using Python and Java. • Collaborate across Agile teams to develop technical solutions for complex geospatial and data-centric challenges. • Participate in software releases, code reviews, CI/CD pipelines, and DevOps processes. • Improve existing applications through performance optimization, automation, and architecture enhancements. • Provide technical consultation and troubleshooting support for software and infrastructure issues. • Collect, integrate, clean, and analyze large-scale geospatial and non-geospatial datasets. • Develop and implement statistical models, machine learning workflows, and geospatial analytics solutions. • Design and maintain scalable data processing pipelines for structured and unstructured data. • Identify trends, anomalies, patterns, and insights within commercial and geospatial datasets. • Develop interactive visualizations and mission-focused analytic products for customer stakeholders. • Conduct cloud-based data research and large-scale data processing. • Collaborate with engineering, R&D, and mission teams to develop new analytic capabilities and data products. • Support intelligence, targeting, collection management, geospatial analysis, and activity-based intelligence initiatives.