Forward Deployed Engineer | IFS Copperleaf

We Love AI Jobs; United Kingdom; Remote; GBP 90,000 - 130,000; Full time

Job summary

IFS Copperleaf seeks a Forward Deployed Engineer to deliver AI-powered decision analytics on customer data. You will take prototypes from discovery to production and ensure value within the deal timeline, collaborating with Sales, Product, and Implementation teams.

You will prototype rapidly, scale successful solutions, and feed reusable components back into our platform while maintaining security, reliability, and observability in customer environments.

Qualifications

• Customer-facing and commercial ability.
• Abstraction and reuse: generalize for reusable accelerators.
• AI and agent engineering: LLM, RAG, prompts, memory, and state handling.

Responsibilities

• Own discovery, technical scoping, architecture, implementation, evaluation, production adoption for strategic customer solutions.
• Prototype aggressively; productionize deliberately using customer data.
• Turn validated customer needs into reusable accelerators and input for product roadmap.
• Collaborate with Product and R&D to update specifications and align with business value.
• Build, deploy, and evaluate solutions; measure adoption and impact across workflows.

Skills

LLM application development

RAG

Prompt engineering

Context engineering

Agent orchestration

Python

Angular

SQL

REST APIs

Tools

Claude Code

Job description

This customer-facing engineering role helps strategic accounts apply IFS Copperleaf’s AI-powered decision analytics to their own data. You will take solutions from discovery and prototyping through production adoption, while bringing validated customer needs back to Product and R&D.* Full-time* Fully Remote### Skills and expertiseLLM application developmentRAGPrompt and context engineeringAgent orchestrationPythonAngularSQLREST APIs### Key responsibilities* Own discovery, scoping, implementation, evaluation, and production adoption for strategic customer solutions.* Build and evaluate prototypes using customer data, then measure workflow impact and value.* Turn validated customer needs into reusable accelerators and product roadmap input.## How this job comparesCompared with 329 open mid-level machine learning jobs on October 10, 2026.Similar open jobs: We Love AI Jobs lists 329 open mid-level machine learning jobs at 145 companies.Remote work: This job is remote. 66 of the 329 mid-level machine learning jobs (20%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. The role requires hands-on LLM application development, RAG, prompt and context engineering, and agent orchestration. It also names Claude Code as a daily engineering tool.## Full descriptionJob DescriptionAbout IFS CopperleafIFS Copperleaf helps the world’s largest asset-intensive organizations — utilities, energy, water, transportation, and more — decide where to invest billions in capital to deliver the most value, using AI-powered decision analytics. Our customers defend and optimize the infrastructure that societies depend on.The RoleAs a Forward Deployed Engineer, you sit cross-functionally across the Sales, Product, R&D, and Implementation teams. For our most critical pursuits, you stand up our current product on the customer’s own data, fast, to prove value inside the deal. And when a customer needs something our product does not yet do, you use modern AI tools to rapidly prototype a near-production ready solution and put it in front of them. You turn “we can’t do that” into “here’s how,” and the strongest prototypes go on to shape our roadmap.You own the technical outcome from discovery through production adoption. Your job is to win deals by delivering fast and with value in the current production environment, prototyping and articulating value from customer requirements, measuring and proving value across customer workflows, and continuously coordinating field-observed customer needs, ideas, roadmaps, and visions with the product and sales organizations. You are the shaper that understands customers’ needs, hypothesizes on value, co-creates the solution, and can test, measure, and validate the outcomes.What You Will Do• Work alongside Solutions Consultants and Account Executives with our most innovative and strategic accounts as well as our most important net new opportunities.• Own discovery, technical scoping, architecture, implementation, evaluation, productionization, adoption, and handoff for strategic customer solutions. Deploy and prove value.• Prototype aggressively; productionize deliberately.• For sales and product management validation, build the smallest safe prototype that tests the hypothesis inside the deal’s timeline. For production use, engineer for security, reliability, observability, maintainability, and integration with the customer’s architecture.• Build, deploy, and evaluate with customer data; measure adoption, workflow impact, reliability, and time-to-value; iterate with technical and business stakeholders.• Partner closely with Product and R&D to turn validated customer patterns and production evidence into supported roadmap investments, reusable components, and platform improvements.• Turn recurring needs into reusable accelerators so the whole team moves faster.• Develop solution specifications with the customer to feed product and engineering organizational understanding, continuously updating the specification as the solution and outcomes evolve.• Work with Product continuously as business value emerges and outcomes become known to evaluate business potential, broader market needs, competitive differentiation aspects, and functional/technical specifications.How We Measure This Role• Influenced ACV on deals where an FDE engaged.• Time to first working prototype on the customer’s own data.• Graduation rate: the share of prototypes that reach production.• Patterns and accelerators shipped, and how often they get reused on later engagements.• Recurring gaps taken to Product, and what Product decided.QualificationsWhat You BringRequired• Customer-facing and commercial ability. You can run a technical discovery session, hold a value conversation with both technical and business stakeholders, and connect what you build to the customer's outcome and the deal's value case. The ultimate value of this role is connecting technology to real business outcomes.• Abstraction and reuse. You can generalize what you built for one customer into a reusable accelerator the team applies on the next engagement.• AI and agentic engineering. LLM application development, RAG, prompt and context engineering, and agent orchestration, including the judgment for when to use single versus multi-agent patterns and how to handle memory and state. Modern AI coding tools such as Claude Code as daily practice, not novelty.