Forward Deployed Engineer

Sand Tech Holdings Limited

42d•Hybrid

About The Position

Build AI that matters in the world. At Sand, Forward Deployed Engineers (FDEs) use AI, data and software to solve problems that have consequences far beyond a screen. In this role, you will work inside some of the world’s most complex operational environments, alongside the people who run them: turning messy data and ambitious ideas into solutions that deliver measurable results and improve people’s lives. You won’t spend months building against a distant specification. You’ll get close to the problem, prototype quickly, deploy into production and see the impact of what you build. If you want to apply advanced technology to meaningful problems; and work with exceptional colleagues who are as ambitious, curious and practical as you are, this could be the role for you.

Requirements

Have 3–5+ years of experience as a Data Scientist, Data Engineer, ML Engineer, Software Engineer or in a similarly technical role.
Have built solutions using complex, imperfect, real-world datasets.
Can move confidently between understanding a problem, writing code, testing with users and deploying a working solution.
Have experience working directly with customers, operators or business stakeholders.
Communicate clearly with both highly technical and non-technical audiences.
Are comfortable making progress without a perfect brief or established playbook.
Take ownership of outcomes and remain resourceful when you encounter constraints.
Want your technical work to create visible, meaningful impact in the physical world.
Are excited by significant travel and spending time embedded with customers.
Strong programming ability, preferably in Python, together with SQL and modern data tooling.
Data ingestion, transformation and pipeline development.
APIs, cloud environments and enterprise data architectures.
Applied machine learning, optimisation, simulation or operations research.
Modern AI development, including LLM applications, agents, retrieval and evaluation.
Data visualisation and rapid application or prototyping frameworks.
Deploying, monitoring and iterating production solutions.

Nice To Haves

Preference for front-end product engineering capabilities (including Typescript).
Experience in energy, utilities, healthcare, telecommunications, government or another asset-intensive industry is valuable, but not essential.

Responsibilities

Embed within customer teams to understand their operations, constraints and highest-value problems.
Translate complex operational challenges into clearly defined technical opportunities.
Use rapid analysis, prototyping and iterative validation to prove value within weeks rather than months.
Establish clear success measures and demonstrate tangible financial, operational or societal impact.
Design and deploy models, pipelines, dashboards, optimisers, AI agents and operational tools.
Turn fragmented, imperfect real-world data into reliable products and actionable intelligence.
Work through data-access, integration, security and workflow constraints without losing momentum.
Build with a production mindset, balancing speed with reliability, maintainability and responsible use.
Work directly with operators, engineers and senior stakeholders to build trust and sustain momentum.
Translate technical concepts into clear decisions and practical actions.
Test solutions with users, incorporate feedback quickly and ensure the tools you build become part of day-to-day operations.
Train client teams and transfer knowledge so solutions continue creating value after deployment.
Capture reusable patterns, components and workflows from field deployments.
Work closely with Product and Platform Engineering to turn customer learning into stronger platform capabilities.
Surface recurring technical gaps and help prioritise the product roadmap.
Ensure each deployment makes the next one faster, stronger and more scalable.
Recognise where successful work could solve additional client problems or create value at greater scale.
Bring field intelligence into the development of new enterprise AI propositions.
Support the shaping and technical scoping of follow-on projects.
Help turn strong initial delivery into long-term strategic partnerships.