HSO Group B.V. - Forward Deployed Engineer
Requirements
• We’re looking for experienced engineers who combine strong technical depth with commercial awareness and the ability to operate confidently with customers. • You’ll ideally bring: • Significant experience across software engineering, cloud engineering, data engineering, solution development, technical consulting or enterprise technology delivery, with senior level ownership of complex solutions. • Strong hands on experience building and operating production grade solutions on at least one major cloud platform. • Strong understanding and practical experience of modern enterprise data platforms, including data architecture, integration, transformation, governance and the role data plays in enabling AI and application workloads. • Experience with Microsoft data technologies such as Microsoft Fabric, Azure Data Factory, Azure Synapse, Azure Databricks, OneLake or comparable enterprise data platforms would be highly valuable. • Excellent coding capability in a modern language such as Python, C#, TypeScript, JavaScript or Java, with a track record of producing maintainable, production quality software. • Practical experience designing, building and deploying AI powered applications using platforms such as Azure AI, OpenAI, AWS Bedrock, Google Vertex AI, Anthropic or comparable technologies. • Hands on experience with large language models, prompting, retrieval augmented generation, evaluation and agent orchestration. • Strong understanding of APIs, integrations, data platforms and modern distributed application architectures. • Experience with modern engineering and DevOps practices including CI/CD, automated testing, source control and infrastructure as code. • Strong customer facing experience in consulting, transformation, delivery or technical leadership. • The ability to work effectively where requirements are incomplete, priorities evolve quickly and the right answer is not immediately obvious. • The judgement to balance engineering excellence with speed, practicality and customer value. • You do not need to be an expert in every technology we use. More important is the ability to learn quickly, understand unfamiliar environments and apply strong engineering and data fundamentals to new problems. • Certifications across Microsoft Azure, Microsoft Fabric, AWS, Google Cloud or leading AI platforms. • Experience working with enterprise platforms such as Dynamics 365, Power Platform, Salesforce, SAP, ServiceNow or similar. • Experience implementing responsible AI, AI governance, evaluation frameworks or model monitoring in enterprise environments. • Experience designing or delivering modern data platforms that support analytics, operational applications or AI workloads. • Experience across industries such as Manufacturing, Retail, Financial Services, Public Sector or Professional Services. • A track record of turning successful customer solutions into reusable patterns or accelerators. • Experience leading small, highly capable engineering teams from discovery through to production.
Responsibilities
• Own Customer Outcomes • Embed rapidly within customer teams and develop a strong understanding of their priorities, operating processes, systems, data and constraints. • Translate ambiguous business problems and defined customer outcomes into clear technical delivery plans. • Act as the technical lead throughout an engagement, guiding customer sponsors, business users, technical teams and HSO colleagues towards successful delivery. • Build trusted relationships with senior operational and technical stakeholders, including CTO and CIO level leaders. • Take ownership for delivering solutions that create measurable customer value rather than simply completing technical tasks. • Lead Discovery and Solution Design • Lead technical discovery workshops to understand customer challenges and identify high value AI, data and automation opportunities. • Assess business processes, data readiness, data architecture, integration points, security requirements, technical risks and operational constraints. • Understand the customer’s existing data platform landscape and identify how data needs to be accessed, transformed, governed or modernised to support the required solution. • Apply a problem first approach to identify the smallest valuable solution that can be built and proven quickly. • Design end to end solution architectures that balance speed, scalability, maintainability, security and responsible AI. • Turn discovery into a pragmatic roadmap from prototype through to production. • Build and Ship Production Solutions • Design, build, integrate, test and deploy enterprise grade solutions using modern cloud, data and AI technologies. • Develop AI powered applications, copilots, agents, automations, integrations and workflow solutions. • Build solutions that make effective use of modern enterprise data platforms and ensure AI applications are supported by reliable, governed and accessible data. • Integrate solutions with platforms such as Microsoft Fabric, Azure Data Services, Dynamics 365, Power Platform, Salesforce, SAP, ServiceNow and customer owned systems, APIs and data platforms. • Apply modern engineering practices including source control, CI/CD, automated testing, infrastructure as code, observability and secure development. • Work iteratively. Deliver value quickly, learn from real world usage and progressively harden solutions for enterprise production. • Design and implement robust agentic workflows, human in the loop processes and, where appropriate, multi agent architectures. • Apply modern techniques across retrieval, grounding, orchestration, tool integration, context engineering and evaluation. • Build evaluation frameworks and guardrails to test AI behaviour, reliability and quality before and after deployment. • Implement appropriate responsible AI, security, monitoring and governance controls. • Ensure data quality, lineage, governance and availability are considered as fundamental components of AI solution design. • Use operational data and user feedback to continuously improve solution quality and performance. • Create Reusable HSO Capability • Reuse existing HSO assets, accelerators and delivery patterns wherever they improve speed and quality. • Turn lessons from customer engagements into reusable assets, reference architectures, engineering patterns and playbooks. • Contribute actively to HSO’s AI, Data, Frontier and Horizon engineering communities. • Share practical knowledge across regions, practices and delivery teams. • Support and mentor other engineers as the Forward Deployed Engineering capability grows.
Benefits
• AI is changing how organisations operate, but most businesses do not need more demonstrations or isolated pilots. They need people who can identify where AI will genuinely create value, ensure the underlying data foundations are fit for purpose and then build something that works in production. • That is what this role is designed to do. • As a Forward Deployed Engineer at HSO, you’ll work directly with strategic customers at the point where emerging AI, data and cloud capabilities meet real business problems. • We offer a competitive base salary alongside HSO’s standard employee benefits. • The role will also include a performance related element designed to recognise both individual contribution and the value created through successful customer delivery. Further details on the compensation structure and performance measures will be discussed during the recruitment process.
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