HBX Group is the world’s leading technology partner, connecting and empowering the world of travel. We’re game-changers, disruptors, the people who bring together local and global brands in accommodation, transport, activities and payments through our network of 300,000 hotels worldwide, 60,000 hard to reach high value clients such as tour operators, travel agents and loyalty schemes across 140 source markets. We are tech-driven, with a customer-first philosophy, and commercial teams whose knowledge and relationships on the ground are second to none.
Job summary
The Senior Engineer for Sourcing vertical is the technology owner responsible for the strategy, architecture, delivery and operational excellence of the Data, Analytics, Machine Learning and Artificial Intelligence solutions supporting the Sourcing domain. As one of the most strategically important domains within HBX, Sourcing is responsible for delivering the capabilities that optimize supplier acquisition, commercial performance, hotel engagement, fraud prevention and intelligent decision-making across the business.
The role provides technical leadership across multiple engineering teams and is accountable for ensuring that Sourcing data products, analytical solutions, ML models and AI-driven services are scalable, reliable, secure and aligned with business priorities. Acting as the senior technology authority for the domain, the Senior Engineer drives the evolution of the Sourcing ecosystem, governs architectural standards and ensures the successful delivery and operation of business-critical capabilities that directly contribute to revenue growth, margin improvement and operational efficiency.
The Senior Engineer serves as the bridge between Product, Engineering, Business and Executive stakeholders, translating strategic business opportunities into scalable and sustainable technology solutions. The role is responsible for ensuring the successful execution of HBX's most impactful Sourcing initiatives, including supplier optimization, contract intelligence, fraud detection, incentive management, intelligent routing and other advanced analytics and AI-driven capabilities.
Through close collaboration with Product leadership and Executive stakeholders, the role ensures that the Sourcing domain continues to deliver measurable business value while supporting the company's long-term growth strategy. As data, analytics, Machine Learning and Artificial Intelligence become increasingly critical competitive differentiators, this position plays a key role in enabling HBX to scale its commercial and sourcing capabilities while maintaining operational excellence and technology sustainability.
Position Responsibilities
- Own end-to-end responsibility of the Sourcing Domain services, ensuring alignment with business objectives and technology strategy.
- Lead the design and delivery of Data, ML and AI solutions that support supplier acquisition, commercial performance, revenue growth and operational excellence.
- Ensure all IOS solutions are scalable, reliable, maintainable and aligned with business priorities and company strategy.
- Act as the senior technology authority for the Sourcing domain, defining engineering standards, architectural principles and solution design best practices
- Drive the continuous evolution of data-driven capabilities across the domain, identifying opportunities to increase automation, efficiency and business value
- Ensure platform scalability, reliability, security, maintainability and cost-efficiency as business demand grows.
- Build strong relationships across Product, Data Science, Engineering and Business teams to ensure alignment and successful execution communicating strategy, progress, risks and investment requirements effectively to senior stakeholders.
- Assume end-to-end ownership of sourcing data services and solutions operating in analytics production environments.
- Ensure the reliability, performance and availability of business-critical analytical, ML and AI services.
- Establish and monitor service KPIs, operational metrics and performance indicators within their responsibilities.
- Lead incident resolution, root cause analysis and continuous improvement initiatives when production issues occur.
- Ensure operational readiness and long-term sustainability of all delivered solutions.
- Promote experimentation and innovation while ensuring solutions deliver measurable business value.
- Drive adoption of advanced AI techniques, optimization algorithms and intelligent decision-making capabilities across the organization
Required skills
- Exceptional leadership skills with proven ability to lead multiple engineering teams through Team Leads and senior technical contributors.
- Strong stakeholder management capabilities, with experience engaging and influencing Director and C-Level stakeholders.
- Strong business acumen with the ability to understand commercial challenges and translate them into scalable Data, Analytics, Machine Learning and AI solutions.
- Outstanding communication and presentation skills, capable of explaining complex technical concepts to both technical and non-technical audiences.
- Strategic mindset with the ability to align technology investments and engineering priorities with business objectives.
- Proven ability to lead large-scale, cross-functional initiatives involving Engineering, Product, Data Science and Business teams.
- Strong decision-making and prioritization skills in fast-paced environments with competing priorities.
- Ability to balance innovation, experimentation and long-term platform sustainability.
- Strong people leadership capabilities, including coaching, mentoring and capability development.
- Demonstrated experience building high-performing engineering organizations and fostering a culture of ownership and continuous improvement.
- Excellent analytical and problem-solving skills.
- Resilience and ability to operate effectively under pressure while managing business-critical initiatives.
- Strong command of English, both written and verbal.
- Deep understanding of Machine Learning, Artificial Intelligence and predictive analytics solutions in production environments.
- Experience delivering and scaling business-critical ML and AI solutions that generate measurable business impact.
- Strong understanding of supervised and unsupervised learning techniques, recommendation systems, optimization algorithms and predictive modelling.
- Familiarity with Generative AI concepts, LLM-based solutions and AI-assisted decision-making systems.
- Proven experience building, deploying and operating Machine Learning solutions in production.
- Strong understanding of MLOps practices including model deployment, monitoring, retraining, versioning and lifecycle management.
- Experience designing scalable ML pipelines and automated model delivery frameworks.
- Experience implementing observability, performance monitoring and reliability controls for production ML services.
- Strong understanding of modern data architectures supporting Analytics, ML and AI workloads.
- Experience working with cloud-based analytical ecosystems including Snowflake, dbt and modern ELT frameworks.
- Strong knowledge of data integration patterns including batch, streaming, APIs and event-driven architectures.
- Experience supporting enterprise analytical platforms and data products consumed by multiple business domains.
- Strong software engineering background with expertise in Python.
- Strong SQL skills and experience working with large-scale analytical datasets.
- Understanding of software design principles, testing frameworks and engineering best practices.
- Extensive experience with AWS cloud services and cloud-native architectures.
- Experience with containerized environments and deployment automation.
- Knowledge of CI/CD pipelines, Infrastructure as Code and DevOps practices.
- Experience collaborating with Product Managers and Data Science teams to transform prototypes into production-ready solutions.
- Ability to assess technical feasibility, scalability and business value of AI initiatives.
- Experience managing the full lifecycle of AI-enabled products from concept to production operation.
Experience & Qualifications
- 10+ years of experience in Software Engineering, Data Engineering, Machine Learning Engineering, AI Engineering or related technology leadership roles.
- 5+ years of experience leading engineering teams, engineering managers or technical leads within enterprise environments.
- Proven experience delivering business-critical solutions in production environments.
- Demonstrated experience leading large-scale initiatives involving multiple engineering teams and stakeholders.
- Strong track record of successfully delivering strategic projects from concept through production deployment and operational ownership.
- Experience working closely with Product Managers, Data Scientists and Business stakeholders to translate business requirements into scalable technology solutions.
- Proven experience managing complex delivery roadmaps, balancing strategic initiatives, operational responsibilities and technical debt.
- Experience owning and operating services with demanding availability, reliability and performance requirements.
- Experience managing relationships with senior business and technology stakeholders, including Directors and C-Level executives.
- Strong command of English. Must be able to hold technical & functional conversations fluently.
At HBX Group, we believe that diversity drives innovation and makes travel a force for good. We’re committed to creating an inclusive workplace where everyone feels valued and respected, embracing different backgrounds, perspectives and talents. Join us and be part of a team where diversity and equal opportunities really do make a difference.