Sr. Software Engineer

Senior Software Engineer At Procure Analytics, we are passionate about driving continuous value for our 800+ members, and we are passionate about doing so with cutting-edge technology. Headquartered in Atlanta, Georgia, USA, Procure Analytics is the leading tech-enabled global purchasing organization for MRO and Packaging, leveraging $1B+ in buying power to achieve up-front and ongoing savings for member companies. The Company was founded to address the complex challenges of a frequently ignored indirect spend category – Maintenance, Repair and Operations Supplies (MRO) and packaging. The nature of MRO supplies (millions of SKUs, thousands of individual transactions, hundreds of potential suppliers, and the relatively small cost for individual products) make MRO an under-managed category within most organizations. MRO comprises 1-3% of most companies' total purchases. In the last decade, Procure Analytics has grown from 2 employees and $5 million in total managed spend to over 100 employees and more than a billion dollars in spend, while maintaining its high-touch service model and member-focus. Procure Analytics has continued to evolve, adding new categories and geographies in response to members' needs. Procure Analytics is the fastest growing company in its sector. Procure Analytics' team serves as an extension of their member organizations, leading change management, driving adoption, and increasing compliance at member locations, while providing analytical tools, savings reporting, and buyer training to drive continuous value growth for mid-size to Fortune 500 companies. These services, resources and data analytics are provided at no cost to members. Procure Analytics has a very collaborative, humble, and values-driven culture that upholds these guiding principles: Act with integrity and in compliance Drive value creation Be disciplined entrepreneurs Be innovative Treat others with dignity and respect In December 2021, Genstar Capital invested in Procure Analytics, along with a large rollover from Bregal Sagemount and the management team. Genstar Capital is a leading private equity firm that has been actively investing in high-quality companies for over 30 years. Based in San Francisco, Genstar has developed a strong market reputation of working in partnership with management teams and its network of strategic advisors to build industry-leading businesses while generating outsized returns. Genstar's vision is to help build lasting, impactful companies that will continue to succeed well beyond their ownership. The Company had previously been backed successfully by Bregal Sagemount, who rolled a significant equity stake into the new investment to continue with the company as a minority investor. As a Senior Software Engineer, you will design, build, and maintain the internal and member-facing software that powers our analytics, reporting, and procurement tools. You will write production code yourself and own the architecture of the systems you build, making sure they are scalable, secure, and built to last. You will also lead how we use AI-assisted development tools, including Claude Code, and how our AI integration layer connects assistants to internal and third-party data. Those tools speed up our work, but they do not replace engineering judgment. Every change must be correct, secure, tested, and maintainable before it ships. Responsibilities include: Design, develop, and maintain production applications, services, and data pipelines that support our members and internal teams. Own software architecture for assigned systems: define service boundaries, data models, and integration patterns, evaluate tradeoffs, and document design decisions clearly. Use Claude Code and other AI-assisted tools to accelerate development, and review, test, and validate all generated code for correctness, security, and maintainability before it is merged or deployed. Build, maintain, and extend MCP servers and integrations that connect AI assistants to internal and third-party data sources, with authentication and least-privilege access built in. Establish and enforce engineering standards for code quality, testing, code review, security, and documentation across the team. Lead security design and review for new features and data flows, including threat modeling, authentication and authorization design, access control, data protection, and review of AI-generated code for security weaknesses. Apply secure development practices across the software lifecycle: follow secure coding standards, manage secrets and access credentials properly, scan dependencies for vulnerabilities, and remediate findings promptly. Build and maintain automated test suites, CI/CD pipelines, and deployment processes, including automated security checks as release gates. Design and build integrations with cloud platforms and third-party systems, including authentication, identity providers, and secure API access. Diagnose and resolve complex production issues and conduct root cause analysis to prevent recurrence. Work with business stakeholders to translate requirements into well-scoped, well-engineered solutions. Mentor engineers on coding practices, AI-assisted development workflows, data engineering, software design, and secure development. Location Atlanta, GA (Hybrid Schedule: Onsite Monday through Thursday, and work from home on Fridays) The Person We are looking for a hands-on software engineer who writes, reviews, and ships code daily, and who ensures our applications, data systems, and AI-assisted development output are accurate, secure, and production-ready. With the breadth of technologies we use, the successful candidate will manage multiple priorities, make sound tradeoffs, and communicate those tradeoffs clearly to both technical and non-technical colleagues. Time allocation for this role is approximately 45% building and maintaining software and data pipelines, 20% reviewing, testing, and validating code (including AI-generated code and security validation), 20% architecture, design, and technical planning, and 15% mentoring, documentation, and cross-team collaboration. Requirements Successful candidates should have: Ten or more years of professional software engineering experience, including hands-on development of production systems and data pipelines. Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience. Strong proficiency in full-stack development, including modern front-end development (such as React with TypeScript) and a back-end language and its ecosystem (such as Python, C#, or Java). Solid understanding of software design principles, data structures, algorithms, and database design (SQL and/or NoSQL). Proven software architecture skills, with experience designing or leading the design of large-scale enterprise applications, including service boundaries, data models, integration patterns, and non-functional requirements such as scalability, reliability, and security. Strong security awareness in code development: working knowledge of secure coding practices (such as the OWASP Top 10), authentication and authorization design, data protection, secrets management, and dependency and vulnerability management, with experience leading security reviews or threat modeling. Experience implementing authentication and authorization with enterprise identity providers (OAuth 2.0, OpenID Connect, SSO). Demonstrated experience writing automated tests, including unit and integration tests, and building CI/CD pipelines. Experience with version control (Git) and collaborative code review workflows. Familiarity with Jira and Confluence for tracking and managing work, and maintaining technical documentation. Experience with cloud platforms, preferably Microsoft Azure or another major cloud provider. Hands-on experience using AI coding assistants such as Claude Code, with a clear understanding of their strengths and limitations. Experience building or integrating with Model Context Protocol (MCP) servers, or with other tool-use and API integration patterns for AI assistants. A strong eye for code quality, security, and edge cases, with the discipline to verify AI-generated output rather than accept it at face value. Ability to write clear technical documentation and design notes. Excellent verbal and written communication skills. Detail oriented, with strong follow-through on commitments. Preferred: Experience designing systems for reliability, observability, and performance at scale. Experience with data analytics, reporting, or procurement systems. Experience with data warehousing or large-scale ETL/ELT platforms. Experience establishing engineering practices or standards for a team. Experience building production MCP servers or other AI tool integrations. Procure Analytics