Engineering Manager

Reporting to the VP of Engineering and Delivery, the Engineering Manager will lead and manage all engineers on our Task team and Communications & Engagement teams.  

As a senior technical leader, you will be accountable for the delivery of releases and hotfixes for our StoreForce SaaS application, ensuring engineering excellence through hands-on code reviews and enforcement of coding standards. A critical aspect of this role is driving significant developer productivity gains through AI-powered coding tools, championing our strategic initiative to achieve 60% productivity improvements by leveraging AI and fundamentally rethinking how we develop software.

RESPONSIBILITIES

1. Technical Leadership & Engineering Excellence

• Lead engineering resources, providing hands-on technical guidance and direction.

• Conduct thorough code reviews ensuring adherence to engineering standards, best practices, and architectural guidelines.

• Enforce engineering standards including unit test coverage, code quality metrics, documentation, and coding conventions.

• Mentor senior engineers and technical leads, fostering technical excellence throughout the organization.

• Participate in technical design discussions, providing expert guidance on approach, architecture, and implementation.

• Champion continuous improvement in engineering practices, tools, and processes.

2. AI-Driven Productivity & Developer Performance

• Drive adoption of AI-powered coding tools across engineering teams to achieve 60% productivity gains.

• Serve as the organization's champion and expert for AI coding technologies with hands-on proficiency.

• Lead the transformation of development practices, rethinking traditional approaches to leverage AI capabilities.

• Provide training, mentorship, and best practices on maximizing AI coding assistants.

• Leverage JellyFish analytics to measure, track, and optimize team productivity, AI adoption rates, and efficiency gains.

• Use JellyFish data to identify bottlenecks, set improvement targets, and demonstrate ROI from AI investments.

• Stay ahead of the AI coding landscape, evaluating new tools and techniques for adoption.

3. Delivery Management & Accountability

• Take full accountability for delivery of all StoreForce SaaS application releases and hotfixes.

• Collaborate with project manager, own the end-to-end delivery process, ensuring releases meet quality, timeline, and stakeholder requirements.

• Collaborate with project manager, manage release planning, scheduling, and coordination across distributed teams.

• Provide accurate insights into workload, effort estimation, and delivery timelines.

• Proactively identify and mitigate risks impacting delivery schedules or quality.

• Collaborate with project manager and devops, manage hotfix prioritization and deployment, ensuring rapid response to critical production issues.

4. Team Leadership & People Management

• Provide mentorship and support, fostering a positive and collaborative work environment.

• Set clear objectives, monitor progress, and conduct regular performance evaluations.

• Recruit top technical talent with aptitude and enthusiasm for AI-assisted development.

• Identify training needs particularly AI coding tools and technical skill development.

• Build and maintain a high-performing, cohesive team culture across geographic boundaries.

5. SDLC Management & Quality

• Own the SDLC process, ensuring effective management and continuous improvement

• Implement and enforce software development best practices: coding standards, mandatory code reviews, unit testing requirements, test coverage targets, documentation standards, and version control strategies.

• Ensure comprehensive unit test coverage across all code changes.

• Drive initiatives to address technical debt and improve system maintainability.

• Maintain and secure code repositories, managing version control processes effectively.

  
  

6. Collaboration & Issue Resolution

• Foster strong working relationships with Systems Architect, DevOps Manager(s), and cross-functional teams (QA, Product, Deployment).

• Provide regular updates to VP of Engineering and Delivery on delivery status, risks, and team performance.

• Demonstrate urgency in resolving critical production issues per service level agreements.

• Lead post-mortem analysis of significant issues, implementing preventive measures.

  
  

QUALIFICATIONS

Competencies Required:

• Technical Leadership - Recognized technical expert who leads by example with meaningful code reviews and constructive guidance

• AI Advocacy - Passionate evangelist for AI-assisted development with vision to transform software development approaches

• Leadership - Motivational and supportive role model who fosters cooperation and collaboration

• Accountability - Takes ownership of delivery outcomes and follows through on commitments

• Communication - Excellent oral and written skills, able to adapt to technical and non-technical audiences

• Problem Solving - Distinguishes between symptoms and causes; identifies root issues and generates solutions

  
  

EXPERIENCE / KNOWLEDGE

• Bachelor's degree in Computer Science, Software Engineering, or related field (Master's a plus)

• 8-10 years software development experience with 5+ years in technical leadership or management roles

• Hands-on experience with AI-powered coding tools (GitHub Copilot, Cursor, Amazon CodeWhisperer, etc.) with demonstrated productivity gains

• Proven track record driving AI adoption across engineering teams and evangelizing new practices

• Experience with engineering productivity platforms such as JellyFish or similar analytics tools

• Strong hands-on experience with Microsoft technologies: .NET, ASP.NET, .NET Core, Azure, SQL Server

• Proven track record leading distributed teams across multiple locations and time zones

• Experience conducting code reviews and establishing engineering standards in production environments

• Deep understanding of software testing practices including unit testing and test automation

• Experience managing evolution of monolithic architectures and addressing technical debt

• Proven success delivering SaaS software releases in retail software or similar domains

• Strong experience with DevOps practices and Microsoft DevOps tools (Azure DevOps, GitHub Actions)

• Experience managing remote and distributed teams is essential

  
  

Key Performance Indicators (KPIs)

• Delivery Excellence - On-time delivery of releases and hotfixes with minimal defects

• Developer Productivity - Measured improvement in productivity metrics via JellyFish (cycle time, throughput, velocity)

• AI Adoption & Impact - AI tool adoption rates, measured productivity gains (targeting 60%), AI usage metrics

• Code Quality - Code review completion, unit test coverage, code quality scores, technical debt reduction

• Release Stability - Post-release defect rates, hotfix frequency, production incident reduction

• Team Performance - Productivity, velocity trends, employee satisfaction, retention rates

• Process Improvement - DevOps adoption, SDLC improvements, automation metrics