Engineering Manager

In this role, you will drive:

• Technical vision and strategy: Make technical decisions and advise the team on the software development approach to take, considering trade-offs between the approaches and mitigating known drawbacks
• Team leadership and development: Lead, mentor, and grow a diverse team of engineers across frontend, backend, DevSecOps, data, and analytics. Foster a culture of continuous learning, experimentation, and improvement. Identify skill gaps and oversee team training and recruitment efforts.
• Cross-functional collaboration: Work closely with Product, Customer Success, Sustainability, and Solution Engineering to align on feature prioritization and roadmap execution. Collaborate with Design to ensure a seamless user experience with intuitive user flows and consistent design throughout the product.
• Software development and project management: Plan and manage the engineering scope, schedules, and quality for each feature and release. Ensure timely and efficient execution across the product lifecycle.
• Technical excellence and delivery: Build and maintain a scalable, high-quality codebase, enforcing coding standards, testing practices, and quality assurance processes, and managing technical debt. Conduct peer code reviews and provide hands-on technical guidance. Streamline workflows by integrating software engineering, quality assurance, DevSecOps, and MLOps frameworks, guidelines and processes into software development activities
• Security and Compliance: Ensure secure coding and existing software development lifecycle guidelines and standards are met. Work with Legal and IT support to ensure the platform is secure and complies with security standards such as ISO 27001 and SOC
• Monitoring and Incident Management: Set up advanced logging and alerting systems to detect and resolve bugs proactively. Develop an incident response plan and lead technical resolution when incidents occur to minimise downtime and impact to customers.
• Infrastructure and Performance: Design and maintain an architecture that supports scalable growth and high availability. Effectively manage cloud infrastructure, and develop strategies to minimize cloud spending, optimizing resource allocation and infrastructure costs. Track and optimise SaaS metrics, such as uptime, response time, latency, and system performance, ensuring a seamless and efficient experience for customers.
• Process improvement and innovation: Evaluate and select third-party tools, platforms, and services (e.g., databases, monitoring tools, security services) that can help accelerate development while maintaining cost-effectiveness. Stay up to date with industry trends, new technologies, and best practices to improve software development processes. Identify opportunities to optimize processes and implement best practices for industrialising AI and machine learning

To succeed in this role, you need to have/ be:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum 10+ years of experience in software development, with at least 3 years managing high-performing distributed engineering teams.
• Prior experience in startups and working with remote teams
• Experience developing a B2B/ Enterprise-grade SaaS platform
• Hands-on technical skills and good competency in the following: (1) JavaScript, React and NodeJS to build scalable and modular web applications using module federations technique; (2) Server-side programming / building scalable web apps in Python; (3) Database technologies such as Microsoft SQL, Oracle, PostgreSQL, and MongoDB; and (4) Container orchestration technologies such as Docker, Kubernetes.
• Familiarity with cloud services, especially in AWS
• Experience with Agile methodologies
• Excellent communication and stakeholder engagement skills
• Data-driven with strong analytical and prioritization skills
• A self-starter with a growth-mindset and proactiveness in working independently to drive toward achieving results

Good to have 🎉:

• An entrepreneurial problem solver comfortable in managing risk and ambiguity
• Experience in AI-related technologies, AI/ML, Data Science, and scaling data science components in production
• Proven track record of people management and being able to develop individuals’ careers and motivation to achieve team’s outcomes