Forward Deployed Engineer | IFS Copperleaf

Description

The company uses AI-powered decision analytics to help large asset-intensive organizations, such as utilities, energy, water and transportation providers, decide where to put capital investment for the most value. Its customers look after infrastructure that society relies on.

This is a new role on a team that sits between sales, product, R&D and implementation.

Responsibilities

• Work across sales, product, R&D and implementation on the most important deals. Deploy the current product on the customer's own data quickly, so the value shows up during the sale.
• When a customer needs something the product cannot yet do, use modern AI tools to build a near-production prototype and show it to them. Strong prototypes can influence the roadmap.
• Work with solutions consultants and account executives on the company's most strategic accounts and its biggest new opportunities.
• Own the technical side of a customer solution from discovery through production adoption and handoff. This includes scoping, architecture, implementation, evaluation and productionization.
• Build the smallest safe prototype that tests a hypothesis within the deal timeline. For production, design for security, reliability, observability, maintainability and integration with the customer's architecture.
• Build and evaluate with customer data. Measure adoption, workflow impact, reliability and time to value, and iterate with technical and business stakeholders.
• Work with product and R&D to turn validated customer patterns and production results into supported roadmap items, reusable components and platform improvements.
• Turn recurring needs into reusable accelerators that speed up the whole team.
• Write solution specifications with the customer and keep them updated as the solution and outcomes change.
• Work with product as business value becomes clear, assessing business potential, market need, competitive differentiation and functional and technical requirements.
• You will be measured on influenced ACV on deals you join, time to first working prototype on the customer's data, the share of prototypes that reach production, and the number of patterns and accelerators shipped and reused. You will also be measured on recurring gaps raised with product and the decisions made.

Requirements

• Required: you can run a technical discovery session and hold value conversations with both technical and business stakeholders. You connect what you build to the customer's outcome and the deal's value case.
• Required: you can generalize a solution built for one customer into a reusable accelerator for the next engagement.
• Required: you have experience with LLM applications, RAG, prompt and context engineering, and agent orchestration. You know when a single-agent or multi-agent design fits, and how to handle memory and state. You use modern AI coding tools such as Claude Code every day.
• Required: you understand enterprise integrations in regulated utility markets. Familiarity with ESRI ArcGIS/Smallworld, IBM Maximo/EAM, SAP/Oracle ERP/PPM and PowerBI/reporting systems is expected. You understand REST and streaming APIs, authentication, and integration with enterprise systems of record.
• Required: you have a background in asset-intensive industries such as utilities, energy or transportation, or in capital and asset investment planning. This is a strong plus but not a hard requirement, since the company trains on the domain.
• Required: you can travel to customer sites as needed, up to about 50% of the time.
• Preferred: you have built and shipped real software and write code others can maintain. You are fluent in Angular, Python or a similar language, and you can work in unfamiliar languages and codebases. You understand SQL, data modeling and pipelines for ingestion, transformation and serving, and you debug imperfect customer data in live environments.
• Preferred: you have depth in production engineering, including observability, performance and operating at scale.
• Preferred: you have customer-facing technical experience, such as solutions engineering, forward deployment, technical consulting, or work at a startup where you wore several hats.
• Preferred: you have deployed AI in enterprise or regulated environments.
• You are a careful listener who cares about understanding the problem and delivering results. You build and prototype quickly, whether you are adapting existing capability or inventing something new.
• You are AI-native and product-minded, and you know what is credible to demonstrate versus what to promise. You can work alongside a deal team without owning the relationship.
• You communicate well across functions, from a junior investment planner to a boardroom executive. You can turn what you built into clear messaging, knowing it can change behaviors, processes and sometimes mindsets.

Conditions

The company supports flexible and hybrid work. Equal opportunity: the company values an inclusive workforce.

AI tools may help screen applications against job-related criteria. Hiring decisions are made by people on the hiring team.