Engineering Manager

As an Engineering Manager at Enhesa, you will lead a team of talented Engineers building modern applications that deliver value with quality to our global customer base, which includes many Fortune 500 companies. You will be the first line of technical challenge for your team: questioning design and technology choices, keeping solutions as simple as the problem allows, and ensuring the team delivers with quality. You will lead how your team uses AI across the software development lifecycle, continuously improving how engineers work with tools like Claude Code. You will play an important role in shaping our technology and helping accelerate our progress towards SaaS excellence. At Enhesa, we prioritize our people, trusting them to deliver and investing in their growth. You will help reinforce this culture by actively coaching your team and supporting their development.

• →Coach and mentor individuals to grow. Dedicate time to regular one-to-one interactions, support individuals in selecting relevant training, set clear objectives, and provide regular feedback.
• →Lead hiring and onboarding for the team, collaborating with HR to ensure technical and cultural fit.
• →Manage stakeholder expectations by clearly communicating team capacity, identifying and communicating risks, and updating on team progress and needs.
• →Collaborate with technical experts and Product Management to plan and prioritize enhancements in line with business needs. 
• →Lead planning, estimation, and prioritization of technical work, keeping plans up to date and meeting delivery objectives.
• →Advocate for an adequate portion of capacity to be allocated to technical initiatives, ensuring technical strategy is aligned with business goals.
• →Translate and communicate technical concepts and solutions to different stakeholders, both technical and non-technical.
• →Review designs and technical proposals and challenge technology and architecture choices where appropriate. Ensure solutions align with Enhesa's architectural patterns, and escalate to Architecture where direction is unclear.
• →Organize and facilitate team ceremonies as Scrum Master, including daily standups, retrospectives, refinements, and planning.
• →Foster a culture of continuous improvement in the team by prioritizing retrospection and following up on improvement actions. 
• →Resolve impediments and blockers for the team.
• →Execute on the Engineering Strategy and other cross-team initiatives. 
• →Prioritize delivering with quality, promoting practices such as shift-test-left, TDD, test automation, and root cause analysis.
• →Manage incidents according to the Incident Management policy, along with technical risks within the team.
• →Own how the team uses AI across the SDLC, from refinement and design through coding, code review, testing, and incident response. Understand how engineers are actually using AI tools, identify where AI is creating risk or friction (review load, test quality, security, over-reliance, inconsistent practices), and lead continuous improvement of the team's AI-assisted workflow.
• →Measure the impact of AI adoption on delivery and quality (e.g., DORA metrics, rework, defect rates) and share effective practices across teams.

Bachelor's degree (or equivalent) in Engineering, Computer Science, or a related field.

6+ years in software development, including at least 4 years hands-on and experience in a senior or lead role reviewing technical designs.

• Demonstrated ability to evaluate technical designs and trade-offs without implementing them yourself: synchronous vs. asynchronous processing, service boundaries, data consistency, failure modes, and operational cost in cloud-based SaaS systems. This role does not require hands-on coding; it does require sound technical judgment.
• Ability to lead large initiatives spanning multiple teams with high complexity.
• Strong knowledge of engineering principles and practices. 
• Proficiency in Agile methodologies, particularly Scrum. 
• Experience with software development lifecycle and project management.
• Current, hands-on use of AI-assisted development tools (e.g., Claude Code) in your own work, and a clear point of view on how AI changes the software development lifecycle: where it helps, where it introduces risk, and how to measure the difference.
• Excellent communication and leadership skills. 
• High levels of professionalism, interpersonal skills, and personal drive. 
• Team player: ability to work on a team in a collaborative environment, sharing information and best practices. 
• Fluent in English. Other languages are an asset. 
• Experience working with SaaS products.