Fullstack AI Engineer (Senior) - IFS Logistics

IFS

6d•Remote

About The Position

IFS Logistics, built and launched as 7bridges and now part of IFS, is an AI-native enterprise logistics platform that unifies transport data, optimises carrier spend, and automates execution. The team is a small, dedicated group within IFS that reports into the commercial organisation rather than central R&D; it delivers pure SaaS with no consultancy work. The Senior Fullstack AI Engineer will own the audit product surface end to end, including checks that identify late deliveries or incorrect carrier charges, the review queue where customers investigate and action findings, and self-service configuration that enables customers to build their own checks. Audit & Visibility is becoming a standalone product. The role sets the product-surface approach, partners directly with the squad’s Product Lead, serves as the squad’s second technical voice, and mentors a Junior Engineer. Although the role’s depth is frontend and product engineering, engineers are expected to work fullstack, including writing Django, designing API contracts, and understanding the BigQuery and dbt work behind the interface. The work includes building an audit review queue capable of handling tens of thousands of findings per tenant; self-service check configuration with previewing and versioning; explainability for incorrect-charge detection, including reproducible evidence of why a charge was flagged and which rate-card version applied; and the Django endpoints, data contracts, and pagination behind these capabilities. The engineer will also shape how agents support audit creation and review, balancing minimal, meaningful human involvement with safeguards for customers’ freight spend. The position is remote, with candidates required to be based in the UK or the Netherlands. IFS also describes hybrid work opportunities and values in-person connection with colleagues in London and Amsterdam.

Requirements

Around five to eight years of experience building and shipping production software.
Strong depth in React, TypeScript, state management, and interaction design at scale.
Experience owning a product surface end to end, including resolving ambiguity and closing open questions independently.
Genuine fullstack capability, including writing Python/Django, reasoning about API contracts, and recognizing when a client-side solution is inappropriate.
Strong interface performance and scale skills, including pagination, virtualisation, and server-side filtering, with the ability to choose based on data volume.
Experience building human-in-the-loop and explainability interfaces, treating auditability as a product feature.
Raises the quality of other engineers’ work through reviews, pairing, and direct feedback.
Willingness and ability to mentor an engineer earlier in their career.
Practical AI-native development experience, using tools such as Cursor and Claude daily, providing agents suitable context, and identifying confidently incorrect output.
Ability to form and communicate a point of view and work through ambiguity.
Must be based in the UK or the Netherlands.

Nice To Haves

Design-system ownership or close collaboration with a designer on a complex data surface.
Experience with Django REST, BigQuery, dbt, Cube Cloud, or GCP.
Production experience with LLM agents, RAG, or evaluations.
Experience shipping an agent that performs real work, such as agentic audit or fulfilment-rule automation, and an instinct to build simulations to validate logic first.
Experience in logistics, supply chain, freight, or a finance-adjacent domain where errors have financial consequences.

Responsibilities

Own the audit review and configuration product surface end to end, resolving open product and technical questions.
Set the approach for the product surface and partner directly with the squad’s Product Lead.
Serve as the second technical voice in the squad alongside the Staff Engineer who leads it.
Build and scale an audit review queue for filtering, triaging, actioning, and evidencing tens of thousands of findings per tenant.
Build self-service audit-check configuration, including customer workflows for creating, previewing, and versioning checks.
Develop explainability for incorrect-charge detection, with reproducible explanations tied to the relevant rate-card version.
Write Django endpoints, design API contracts and data contracts, and implement appropriate pagination behaviour.
Shape agent involvement in audit creation and review, including meaningful human-review points and safety guardrails.
Mentor the Junior Engineer through review, pairing, feedback, and support toward independent delivery.
Raise squad quality standards through code review on merge requests, avoiding direct-to-production changes, and defining acceptance criteria for tickets.
Measure and improve queue performance at the largest tenant’s data volume.
Build interfaces that make auditability and human-in-the-loop workflows understandable and useful.