Lead/Manager Software Engineering

Our client is a global leader in HR technology, delivering an end-to-end SaaS platform supporting the entire recruitment lifecycle with cloud technology, automation, and AI.

Leadership Experience:

• 2+ years as an Engineering Manager, Software Development Manager, Technical Lead, or similar role with direct responsibility for software engineers.
• Proven experience leading agile product engineering teams and managing delivery, capacity, risks, and technical priorities.
• Strong track record of mentoring engineers, managing performance, and supporting career progression.

Technical Expertise:

• Previous hands-on software engineering experience and technical depth to manage experienced engineers effectively.
• Strong understanding of software architecture, APIs, CI/CD, cloud environments, and modern software development practices.
• Good understanding of machine learning and LLM-based technologies and their application within software products.
• Ability to discuss architecture, technical debt, software quality, scalability, and engineering trade-offs with senior technical stakeholders.

Collaboration & Mindset:

• Experience working in distributed, international organizations across European and North American time zones.
• Strong ownership mindset with ability to communicate risks clearly and make pragmatic decisions.
• Practical experience using AI tools such as GitHub Copilot, Claude, Gemini, or ChatGPT within engineering or management workflows.
• Fluent English with strong written and verbal communication skills.

Team Leadership:

• Lead and support a multidisciplinary engineering team of up to 11 Software Engineers, AI Engineers, and Data Analysts.
• Coach team members through regular 1:1s, structured feedback, performance reviews, and individual development plans.
• Build a high-trust environment based on transparency, ownership, constructive feedback, and continuous development.

Delivery & Engineering Excellence:

• Own sprint execution, workload planning, delivery predictability, and proactive risk management.
• Partner with engineers and architects to maintain software quality, address technical debt, and improve engineering processes.
• Ensure the team balances new development with the stability and maintainability of business-critical parsing systems.

Product & Global Collaboration:

• Partner with Product Managers and Product Owners to refine priorities, assess technical complexity, and translate business needs into achievable engineering plans.
• Coordinate with engineering leaders and stakeholders across Europe and North America.
• Ensure engineering initiatives contribute directly to customer value and wider business objectives.

AI & Technology Modernization:

• Guide the evolution of document-processing technologies combining Perl, Python, machine learning, deep learning, and LLM-based approaches.
• Drive practical adoption of AI tools across engineering, testing, development, and team workflows.
• Identify opportunities to modernize legacy solutions without compromising reliability or operational performance.