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Role: Software Engineer
š Location: London Bridge, London, UK
š” Work Setup: Hybrid (4 days/week in office - Mon-Thurs, Friday remote)
š¼ Type: Full-time, Permanent
š Seniority: Senior Level
š Start Date: ASAP (flexible for the right person)
The Mission
Weāre building the next generation of intelligent enterprise systems that help enterprise businesses understand and act on what matters; faster, deeper, and at scale.
Our platform brings together enterprise data, powerful language models, and Agentic workflows to unlock new levels of insight and decision-making. We believe the future of AI isnāt just about the models; itās about the full-stack software architecture that securely orchestrates, processes, and surfaces that intelligence to real-world users.
This is your chance to help shape that foundation.
The Role
As a Software Engineer, youāll help define the core intelligence behind our Agentic platform, designing systems that enable AI to interact meaningfully with complex business environments. You wonāt be boxed into a single layer of the stack; you will own features vertically from the data lakehouse to all the way downstream.
Youāll work at the intersection of natural language processing, data systems, and applied reasoning, executed across a highly deliberate, balanced split between Frontend, Backend, and Data Engineering. This isnāt prompt engineering, nor is this automation at scale. This is building an Enterprise Grade Platform that allows AI to operate inside real businesses and deliver impact autonomously and securely.
You will join a high-velocity, 3ā5 person dev squad executing against an Outcome-Driven Roadmap. You will take Product Requirements Documents (PRDs) and translate them into robust Technical Design Documentsābuilding data pipelines to process data, engineering secure containerised APIs to expose it, and building and maintaining the responsive React user interfaces that our Fortune 500 clients interact with.
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You will join early enough to shape the architecture, and direction of the platform, working directly alongside our Head of Engineering and Lead Data Scientist to turn raw intelligence into hardened enterprise features. This is a role for a systems-minded, product-aware builder. Someone who sees around corners, enjoys unsolved problems, and wants to help define what AI can do when deeply embedded in business operations.
What Youāll Do
- Frontend: Build and maintain responsive, data-dense, and highly intuitive UIs using React, TypeScript, and modern asynchronous state management to surface complex AI states and metrics.
- Backend Systems: Design, deploy, and scale secure, high-throughput microservices and APIs (Python preferred) running on Kubernetes (EKS).
- Data Pipelines: Build and maintain scalable data pipelines within our existing Medallion architecture, focusing on dependency mapping, performance tuning, and idempotency.
- Zero-Trust Infrastructure: Manage the lifecycle of your own components using Terraform, ensuring all network access and data movement strictly adhere to least-privilege IAM and isolated VPC guardrails.
- Structured Execution: Collaborate across the team to write and review Technical Design Docs, and ship production-grade code that passes rigorous enterprise compliance standards.
The Ideal Profile
- The Hybrid Track Record: 3+ years of professional software engineering experience with a proven history of owning features vertically across the front, back, and data layers.
- Core Languages: Strong proficiency in Python (essential for our data and backend stack) paired with deep commercial competence in React and TypeScript.
- Systems Mindset: A strong understanding of distributed systems, concurrency, and API design patterns. You look at data pipelines through the lens of resource optimisation and minimising idle compute costs.
- Execution Velocity: Comfort navigating ambiguity, and executing cleanly within a lean, fast-moving environment.
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Bonus (Not required) Experience
- Orchestration & Lakehouse Depth: Hands-on experience with Dagster or Airflow. You understand data lineage, backfills, schema evolution, and working with columnar data formats like Parquet.
- Cloud & IaC: Direct experience configuring infrastructure via Terraform and deploying containerised workloads to AWS/Kubernetes.
- ML Engineering: Familiarity with model feature stores, experiment tracking (e.g., MLflow), or deploying inference pipelines.
- Enterprise Security Audits: Experience building or working on platforms with SOC2 or ISO27001 accreditation.
Why Join Us
- Be a core member of a lean engineering team where full-stack execution is a massive force multiplier.
- Work on a production-enterprise-grade, highly optimised AWS, Dagster, and Kubernetes stack that avoids traditional technical debt.
- Collaborate with a no-ego, fast-moving team that values deep technical curiosity and autonomous ownership.
- Shape the immediate future of how enterprise organisations interact with and deploy Agentic AI systems.
āIt took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what Iāve been looking for.ā
Jessica, London
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