Forward Deployed Engineer - USA

Sand Tech Holdings Limited

17d•Onsite

About The Position

Forward Deployed Engineers (FDEs) are Sand’s frontline inside our most strategic customers; embedding directly within client teams to unlock data, building lightweight production solutions, and compressing time-to-value from months to weeks. This is not staff augmentation. This is a value-engineering role: hands-on, deeply technical, fast, and focused on proving ROI in real operational environments. As an FDE, you will sit inside one of our US industries—Energy, Utilities, or Public Sector—and be deployed full-time on-site with a client. You will work shoulder-to-shoulder with operators, engineers, analysts, and executives to identify opportunities, access and shape data, prove value through rapid prototyping, and deploy solutions that drive measurable financial and operational outcomes. Your work directly shapes commercial expansion, platform evolution, and the credibility of Sand in the most complex asset-heavy environments. This role is ideal for a technically strong engineer or scientist who thrives in ambiguity, loves solving real-world problems in the field, and has the communication and resilience needed to earn trust inside demanding customer environments.

Requirements

2–6 years experience as a Data Scientist, Data Engineer, ML Engineer, or Software Engineer working with real datasets and operational environments.
Experience deploying solutions in Energy (Oil & Gas, Power), Utilities (Water/Gas/Electric), or Public Sector strongly preferred.
Proven ability to build prototypes and production-grade tools quickly, with minimal dependencies.
Experience working directly with customers, operators, or business stakeholders in fast-paced environments.
Comfort working independently on-site with high ambiguity and high accountability.
Strong coding ability (Python preferred) plus SQL, wrangling, and modern data tooling.
Experience with APIs, cloud environments, data ingestion patterns, and analytical tooling.
Ability to turn messy, real-world data into operational insights and deployed tools.
Experience with visualization tools and rapid prototyping frameworks.

Nice To Haves

Understanding of ML modeling, optimisation, or operations research is a plus (but not required).

Responsibilities

Embed directly inside the client to unlock data, map value streams, and build lightweight production-grade solutions.
Execute rapid analysis, prototyping, and iterative validation using wrangling tools, secure sandboxes, and proven patterns.
Deliver measurable outcomes within weeks—fast deployments, clear ROI proof points, and visible operational value.
Deploy models, dashboards, optimizers, and operational tools that solve high-value client problems in Energy, Utilities, or Public Sector.
Troubleshoot friction: data access, workflows, security constraints, stakeholder blockers—removing obstacles in real time.
Maintain a production mindset: reliability, iteration, and continuous improvement of deployed solutions.
Build deep trust with operators, engineers, and senior stakeholders through hands-on delivery—not slides.
Translate complex technical problems into simple, actionable insights that drive adoption and operational use.
Train users, institutionalize capabilities, and transfer knowledge so the client can sustain value.
Document field patterns, reusable components, and validated workflows that feed into Sand’s product roadmap.
Work with Product Managers and Platform Engineering to generalize what works and escalate gaps in product capability.
Ensure every deployment contributes to reusability, pattern libraries, and cross-vertical knowledge.
Identify expansion opportunities through on-the-ground insights and signal them to the MD and Solutions Director.
Help shape new enterprise AI propositions with real-world field intelligence from Energy/Utilities/Public Sector operations.
Support the Solutions Director in scoping high-value follow-on work.