Software Engineer (1) - Established Senior Engineer

Skills Required

JavaScript, Artificial Intelligence & Expert Systems, Python 1. JavaScript – Ability to develop and maintain JavaScript-based tools or integrations that improve developer productivity and enable AI-powered workflows. 2. Artificial Intelligence & Expert Systems – Ability to apply AI concepts and tools to practical developer workflows, and help teams use them effectively and responsibly. 3. Python – Ability to write Python scripts and applications to automate tasks, integrate AI capabilities, and support developer enablement.

Experience Required

Senior Engineer Exp

Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides. 10+ years in IT; 8+ years in development

Education Required

Bachelor's Degree

Additional Information

***HYBRID / 4 days per week in office*** ***As this is a hybrid position, the customer may request in-person interviews.*** ***Agency employees are required to be onsite from day one, as specified. Please do not submit remote-only candidates. If a candidate plans to relocate, note in the submittal that the relocation will be at the candidate's own expense.***

• Partner with engineering teams to accelerate adoption of AI-assisted software development tools and practices. Based on your team's documented responsibilities, this includes developer enablement, SDLC acceleration efforts, and support of engineering productivity initiatives.
• Build and maintain internal tooling, automation, and integrations that improve the developer experience.
• Develop prototypes, proof-of-concepts, and production-ready solutions leveraging AI development platforms, coding assistants, and agent-based technologies.
• Create reusable templates, reference implementations, and engineering accelerators that can be adopted across development teams.
• Support onboarding, workshops, office hours, and technical enablement activities for engineering teams.
• Work with platform, architecture, and security teams to implement engineering standards and best practices.
• Develop dashboards and reporting capabilities that help measure adoption, productivity, and engineering effectiveness.
• Identify friction points within software delivery processes and implement automation to reduce manual effort and improve efficiency.
• Contribute to SDLC acceleration initiatives spanning requirements, development, testing, deployment, and operations.