Software Engineering Manager (AI-Enabled)

IntelliTrans, (ITL), a subsidiary of Roper Technologies, Inc. (NYSE: ROP) is seeking an AI Enabled Engineering Manager to join our team, hybrid in Atlanta, GA.

Job Summary

The Engineering Manager will lead cross-functional SaaS engineering teams and serve as a transformational leader in how IntelliTrans designs, builds, and delivers software. This role owns the full software development lifecycle (SDLC) across multiple delivery teams and is accountable for Agile execution, engineering quality, release velocity, and team development.

The ideal candidate is an entrepreneurial engineering leader who has moved from hands-on development into management and brings a modern perspective on AI-driven development, including active use of AI-assisted coding tools such as Claude Code, GitHub Copilot, or similar. The position partners closely with the CTO, Chief Architect, and product leadership to align engineering execution with company strategy and customer outcome

Essential Duties and Responsibilities

Essential Duties and Responsibilities include the following. Other duties may be assigned.

Engineering Leadership & Delivery

• Lead and develop multiple software engineering teams across the full SDLC, from planning through deployment and continuous improvement
• Drive Agile/Scrum delivery, sprint cadence, team accountability, and engineering best practices across all squads
• Own program-level delivery planning and cross-team coordination using SAFe, Scrum, or comparable Lean or Agile frameworks
• Establish and enforce engineering standards, coding practices, code review culture, and quality gates
• Set and track key delivery metrics (cycle time, deployment frequency, defect escape rate, lead time) and drive continuous improvement
• Oversee release planning, version management, and coordinated deployment across environments

AI-Driven Development & SDLC Transformation

• Champion the adoption of AI-driven (not just AI-assisted) development workflows, including AI code generation, AI-augmented testing, and AI-driven code review
• Drive hands-on enablement of AI coding tools (Claude Code, GitHub Copilot, Cursor, or similar) across engineering teams
• Lead transformation of the SDLC to incorporate AI at every stage: requirements, design, implementation, testing, and operations
• Evaluate, pilot, and scale emerging AI development tooling to improve team productivity and code quality
• Build a culture of responsible AI use, including code review practices for AI-generated output, prompt engineering literacy, continuous learning, innovation, risk mitigation, and ROI management

People Leadership & Culture

• Recruit, mentor, and develop engineering talent, building a high-performing, collaborative, and psychologically safe team culture
• Conduct regular 1:1s, performance reviews, and growth planning conversations with direct reports and team leads
• Foster an entrepreneurial mindset within teams, encouraging ownership, experimentation, and proactive problem-solving
• Build a culture of accountability, continuous learning, and delivery excellence
• Identify organizational gaps and lead hiring efforts to scale the engineering team strategically

Transformational Initiatives

• Identify and lead transformational engineering initiatives that meaningfully improve delivery speed, system quality, or operational efficiency
• Partner with the CTO and Chief Architect on strategic roadmap execution and technical modernization efforts
• Champion process improvements, toolchain upgrades, and workflow automation to reduce toil and increase developer productivity
• Lead change management for new engineering practices, tools, and ways of working across the organization

Cross-Functional Collaboration

• Partner closely with Product Management to translate business and customer requirements into executable engineering plans
• Collaborate with the Chief Architect and platform teams on architecture decisions, technical debt prioritization, and system design
• Work with QA, Cloud Ops, and IT leadership to ensure integrated delivery, operational readiness, and cross-team alignment
• Represent engineering in leadership forums, customer escalations, and strategic planning discussions
• Build effective relationships with stakeholders across the business to ensure engineering execution aligns with company goals

Quality, Operations & Governance

• Drive engineering quality through testing strategy, automation coverage goals, and shift-left quality practices
• Oversee incident response, post-mortems, and root cause analysis for production issues affecting product delivery
• Ensure compliance with security, privacy, and software governance requirements across all engineering output
• Manage engineering tools, licenses, and resource allocation in alignment with budget expectations

QUALIFICATIONS AND BACKGROUND

Education

Required: Bachelors degree in Computer Science, Software Engineering, or related field

Preferred: Masters degree in Computer Science, Software Engineering, or Business Administration

Experience

Required:

• 7+ years of software engineering experience, with at least 3 years in an engineering management or team lead role
• Demonstrated experience leading SaaS product engineering teams in a fast-paced, Agile environment
• Hands-on background as a software developer prior to moving into management (ideally full-stack or backend)
• Proven experience owning and improving the full SDLC, from story refinement through production deployment
• Practical experience with AI-assisted development tools (Claude Code, GitHub Copilot, Cursor, or equivalent) and a track record of driving their adoption
• Strong command of Agile/Scrum delivery at the team level and experience with scaled frameworks (SAFe, Lean Startup, or similar)
• Experience leading transformational engineering initiatives that delivered measurable business or operational impact
• Track record of recruiting, developing, and retaining strong engineering talent

Preferred:

• Experience leading or closely partnering with QA, Cloud Ops, or IT functions
• Familiarity with Program Increment (PI) planning and large-scale Agile coordination
• Experience in a growth-stage or entrepreneurial SaaS company, including navigating rapid change and resource constraints
• Exposure to AI/ML-enabled product features or data-intensive SaaS platforms
• AWS architecture awareness or cloud engineering background
• Experience building or managing offshore or distributed engineering teams

Skills

Engineering Leadership:

• Lean Startup, Agile/Scrum delivery, SAFe or similar scaled Agile program management
• Full SDLC ownership across planning, development, testing, release, and operations
• Engineering metrics: DORA metrics, cycle time, deployment frequency, change failure rate
• Technical roadmap planning and cross-squad delivery coordination
• Backlog management, sprint planning, and program increment execution

AI-Enabled Development:

• AI code generation tools: Claude Code, GitHub Copilot, Cursor, Amazon CodeWhisperer
• AI-augmented testing, AI-assisted code review, and prompt engineering for development tasks
• SDLC transformation to incorporate AI tooling at each lifecycle stage
• Responsible AI practices: review workflows, quality gates, and governance for AI-generated code

Software Development:

• Hands-on software development background (any major stack; ideally one or more of: .NET Core, Java, Angular, Flutter/Dart)
• RESTful API design, microservices architecture, and cloud-native development patterns
• CI/CD pipeline design and deployment automation (GitLab CI/CD, Jenkins, or similar)
• Source control strategy: GitFlow, trunk-based development, branching and release strategies
• Code quality practices: peer review, static analysis, test automation, and coverage targets

Quality & Testing:

• Test strategy across unit, integration, end-to-end, and performance testing
• Test automation frameworks and shift-left quality practices
• Defect lifecycle management, regression strategy, and release quality gates

Cloud & Infrastructure Awareness:

• AWS core services (compute, storage, networking, managed databases)
• Container basics (Docker, ECS/EKS) and cloud-native deployment patterns
• Observability fundamentals: logging, monitoring, alerting, and incident response

Preferred Technology Environment:

• AWS
• Angular
• Flutter / Dart
• .NET Core
• Java
• Oracle
• PostgreSQL
• Databricks (a plus)

Competencies

Strategic & Transformational Leadership:

• Entrepreneurial mindset with a bias for action, ownership, and driving meaningful change
• Ability to lead transformational initiatives end-to-end, from vision through sustained adoption
• Strong executive presence and ability to represent engineering to senior leadership and external stakeholders
• Strategic thinking balanced with operational discipline and delivery accountability
• Experience identifying and closing capability gaps through hiring, training, and process improvement

AI & Innovation Orientation:

• Genuine enthusiasm for AI-assisted development and a track record of enabling teams to work smarter with AI tools
• Curiosity about emerging engineering tools, workflows, and development paradigms
• Ability to evaluate new technology pragmatically and drive adoption at scale
• Growth mindset and commitment to continuous learning in a rapidly evolving technical landscape

People Leadership:

• Coaching and mentoring approach that develops both technical skills and leadership capacity in others
• Inclusive leadership style that fosters psychological safety, collaboration, and high performance
• Ability to deliver candid feedback constructively and navigate performance conversations with care
• Strong hiring instincts and ability to build diverse, high-performing engineering teams

Communication & Collaboration:

• Excellent written and verbal communication skills; able to make complex technical topics accessible to non-technical audiences
• Skilled at working across functional boundaries with product, design, architecture, and operations partners
• Transparent, direct communicator who keeps stakeholders informed and manages expectations proactively
• Effective in cross-functional forums, leadership reviews, and customer-facing escalation situations

Analytical & Decision-Making:

• Data-driven approach to delivery decisions, quality investments, and team capacity planning
• Ability to balance technical excellence with business pragmatism and delivery urgency
• Sound judgment in navigating technical debt, scope trade-offs, and competing priorities
• Root-cause orientation with a drive to implement systemic improvements rather than workarounds

Professional Excellence:

• Self-motivated with strong ownership, follow-through, and accountability
• Organized and structured approach to managing multiple teams, initiatives, and priorities simultaneously
• Commitment to engineering craft: quality, reliability, maintainability, and security
• Passion for building great products and great teams

IntelliTrans supports workforce diversity and is a committed equal opportunity. / Affirmative action employer.