Engineering Manager

About AI Labb AI Labb is the Data & AI division of TheAppLabb, a technology innovation firm with 18+ years of experience and 750+ applications launched for industry leaders including Suncor, RBC, Petco, and CSA Group. We bridge the gap between AI's promise and business reality, delivering pragmatic AI solutions that create measurable business outcomes. Our Data & AI Talent Services practice provides clients with specialized expertise across AI/ML, Data Engineering, Full Stack, and Mobile development. We are looking for an Engineering Manager to scale this practice while maintaining the quality and culture that sets us apart. Role Overview We are looking for an Engineering Manager to lead and scale our Staff Augmentation practice. You will manage a distributed team of engineers deployed across various client accounts, serving as their primary advocate and ensuring they have the support to perform at their best. Your mission is to turn our staff augmentation efforts into a structured, high-performing practice. You will partner with Account Managers to ensure client satisfaction while building a strong internal culture for consultants who work remotely or embedded in client teams. You will start by managing a team of approximately 10 consultants with a mandate to scale this into a division of 40-50+ people over the next 12 months. Key Responsibilities Team Management & Retention You will conduct regular one-on-ones or squad syncs with all deployed resources to monitor engagement, workload, and wellbeing. When consultants are struggling, you are responsible for identifying the root cause, providing guidance or technical mentorship, and implementing improvement plans when necessary. You will foster a sense of belonging for consultants who may feel disconnected while working on client sites, ensuring they remain connected to AI Labb's culture and mission. Client & Account Coordination You will serve as the technical bridge between our engineering team and client stakeholders. While Account Managers handle commercial relationships, you handle delivery friction. This means translating client feedback into actionable coaching for engineers, helping articulate blockers that originate from client environments, and interfacing with client technical leads when necessary to clarify requirements. You will ensure our consultants are set up for success on every engagement. Hiring & Scaling the Practice You will lead technical interviewing and selection for incoming consultants across AI/ML, Data Engineering, Full Stack, and Mobile domains with support from appropriate experts. You will establish standardized onboarding, reporting, timesheet protocols, and engineering documentation standards across the practice. As the team grows, you will identify and mentor future Engineering Managers who will report to you, building the leadership bench required to scale. Process & Quality Assurance You will define and implement engineering cadences, communication protocols, and quality standards that work across multiple client environments. You will create feedback loops that surface issues early and enable continuous improvement. You will build the operational infrastructure that allows the practice to scale without sacrificing quality. Required Qualifications Experience: 10+ years in software engineering with at least 4 years in a leadership or management role overseeing multiple direct reports. Consultancy Background: Experience working in a services, agency, or staff augmentation environment. You understand the nuances of managing people who report to you but work day-to-day within client organizations. Broad Technical Literacy: You do not need to be a hands-on coder, but you must have solid understanding of the software development lifecycle across multiple domains including AI/ML and Data Engineering, Full Stack development (frontend and backend), and Mobile development (iOS and Android). You should be able to evaluate technical talent, understand delivery challenges, and have credible conversations with both engineers and clients. People Operations: Proven ability to handle difficult conversations, conflict resolution, performance management, and career development for engineers. You have experience retaining talent in competitive markets. Process Mindset: Experience establishing engineering cadences, reporting structures, and operational processes. You have built or significantly improved team operations, not just inherited them. Nice-to-Have Qualifications Scaling Experience: You have grown a team from small to large, navigating the organizational changes required at different stages. Multi-Geography Management: Experience managing distributed teams across different time zones. Technical Recruiting: Direct experience running technical interviews and building hiring pipelines. AI/ML Domain Knowledge: Deeper familiarity with AI/ML projects and the specific challenges of staffing data science and machine learning roles. Success Metrics Retention: Maintain low turnover among deployed consultants relative to industry benchmarks. Client Satisfaction: Achieve consistently high performance ratings from clients regarding consultant output and professionalism. Scalability: Successfully hire and onboard new consultants to meet demand without degrading quality or breaking existing processes. Culture: Build measurable engagement among consultants as reflected in regular pulse surveys and feedback sessions. Why AI Labb Growth Opportunity: You will build and lead a practice from the ground up, with a clear path to scaling a team of 40-50+ consultants. Enterprise Client Base: Our clients include major organizations across manufacturing, retail, financial services, healthcare, and government. Established Foundation: TheAppLabb brings 18+ years of delivery experience and proven operational infrastructure to support your growth. Impact: You will shape how we develop and support engineering talent, directly influencing the careers of dozens of consultants. How to Apply Send your resume along with a brief note addressing one of the following: a time you turned around a struggling consultant or team member, how you built or significantly improved team operations in a previous role, or your approach to maintaining culture and engagement in a distributed team. We want to understand how you think about people and process, not just your technical background. #J-18808-Ljbffr