R&D Coordinator

Job summary

The R&D Coordinator leads two multidisciplinary teams to ensure the quality, predictability, and continuous improvement of the delivery system. They are responsible for translating priorities into executable plans and managing the end-to-end lifecycle from analysis to production follow-up.

Job details

Core Accountability Own the outcome, not only the activity. The R&D Coordinator is responsible for the coordinated performance of both teams and for the quality, predictability, and continuous improvement of their delivery system. Lead two multidisciplinary teams end to end Direct and coordinate two R&D teams comprising developers, DBA, Scrum Master, and quality assurance professionals. Create one shared plan and clear accountability across analysis, development, testing, release readiness, and follow-up. Ensure work does not stall between functions and that ownership remains clear until the expected outcome is achieved. Balance delivery commitments, product health, technical needs, client impact, and team capacity. Plan and deliver predictably Translate approved priorities into executable delivery plans with clear scope, sequencing, dependencies, risks, and ownership. Maintain realistic capacity plans for both teams and make trade-offs visible before commitments are made. Monitor progress, identify variance early, and lead corrective action when quality, scope, schedule, or capacity is at risk. Own quality throughout the lifecycle Make quality a shared responsibility from requirements and design through development, validation, release, and production follow-up. Ensure appropriate test planning, defect triage, root-cause analysis, regression coverage, and release-readiness decisions. Promote documentation of defects, expected behaviour, technical decisions, and reusable test scenarios. Use recurring defects and production issues to drive systemic improvements in engineering and quality practices. Lead people and build capability Set clear expectations and measurable objectives for team members and reinforce individual and collective accountability. Coach employees through regular feedback, development plans, and direct support when performance or role clarity needs improvement. Build collaboration across disciplines while maintaining high standards for ownership, quality, and execution. Improve Abilis R&D operations Help standardize practical R&D processes, working agreements, documentation, and delivery controls across both teams. Define and monitor a concise set of indicators covering predictability, capacity, quality, flow, and product outcomes. Identify repeated delays, bottlenecks, rework, and manual handoffs, then lead corrective improvements. Support the adoption of AI-assisted tools where they create measurable value. Collaborate across the business Work closely with Product Management and the directors to confirm priorities, scope, acceptance expectations, and roadmap alignment before execution. Coordinate with Operations, Support, Professional Services, DevOps, and other stakeholders on incidents, dependencies, release readiness, and client impact. Communicate risks, decisions, changes, and required actions in a direct and timely manner. What Success Looks Like Clients are satisfied because commitments are delivered on time and with consistent quality. Both teams operate with clear priorities, ownership, capacity, and delivery commitments. Risks, blockers, dependencies, and quality concerns are identified early and acted on quickly. Releases are supported by clear readiness criteria, appropriate validation, and documented decisions. Team performance improves through measurable process changes, coaching, and stronger accountability. Stakeholders have a reliable and transparent view of progress, trade-offs, and expected outcomes. Candidate Profile Proven leadership skills with the ability to manage multidisciplinary teams in a fast-paced, evolving environment. Strong expertise in project management, collaboration tools, and agile methodologies. Strong focus on quality, customer outcomes, operational excellence, and the continuous improvement of processes and ways of working. Experience with AI-assisted software development. Clear, direct communication skills and the ability to align technical and non-technical stakeholders. Only selected candidates will be contacted. Harris is committed to an Employment Equity Program and encourages applications from members of designated groups, including women, persons with disabilities, Indigenous peoples, and visible minorities. If you are a person with a disability, assistance with the screening and selection process is available upon request. Harris’ Talent Acquisition team does not use text messages to communicate with candidates or request confidential information. We encourage all candidates to apply directly to posted positions. Candidates who meet the required qualifications will be contacted for an interview by either a Harris hiring manager or a member of the Talent Acquisition team.

What you’ll do

The R&D Coordinator leads two multidisciplinary teams to ensure the quality, predictability, and continuous improvement of the delivery system. They are responsible for translating priorities into executable plans and managing the end-to-end lifecycle from analysis to production follow-up.

Requirements

Candidates must have proven leadership experience managing multidisciplinary teams in fast-paced environments and expertise in agile project management. Strong communication skills and experience with AI-assisted software development are also required.

Listed skills

• Technical Documentation · Preferred
• Quality assurance · Preferred
• Risk Management · Preferred
• Root Cause Analysis · Preferred
• Team Leadership · Preferred
• Project management · Preferred
• Process Improvement · Preferred
• Stakeholder Management · Preferred
• Cross-Functional Collaboration · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Project Management
• Agile Methodologies
• Team Leadership
• Capacity Planning
• Quality Assurance
• Risk Management
• Stakeholder Management
• AI-assisted Software Development
• Process Improvement
• Resource Allocation
• Defect Triage
• Root-cause Analysis
• Technical Documentation
• Cross-functional Collaboration
• Performance Coaching
• Delivery Management

Job areas

• Management & Leadership
• Software
• Technology
• Engineering
• Consulting

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