Senior Software Engineer

About this role

ABOUT IMU BIOSCIENCES

IMU Biosciences has developed proprietary platform technologies that generate and translate vast system-level immune data into actionable insights and tools to drive the development of precision medicines across a variety of diseases. Built on over a decade of research at King’s College London and the Francis Crick Institute, IMU leverages advanced immune profiling with proprietary AI and machine learning analytics to uncover novel clinical immune signatures. IMU continues to establish partnerships with leading pharma and biotech companies to advance disease diagnosis, optimise product selection, and improve patient stratification and monitoring - while also building its own pipeline of innovative products.

ABOUT THE ROLE

IMU is applying cutting-edge immune system science, data engineering, and machine learning to understand human health in a deeper and more actionable way. As our work scales, we are building the platform capabilities needed to make complex biological and computational data structured, traceable, reproducible, and reusable across the organisation.

We are looking for a Senior Software Engineer, Semantics to help build the semantic and metadata capabilities of the core Data Platform.

This is not a standalone ontology or knowledge graph initiative. The role sits directly within the Data Platform team and focuses on building practical platform systems that help scientists, computational immunologists, and engineers work with trusted and well-structured scientific data.

You will work closely with the Computational Immunology team to understand how analytical and machine learning workflows produce data, and help ensure those outputs are consistently structured, versioned, lineage-aware, discoverable, and reusable inside the platform.

A core part of the role is helping turn fragmented scientific and computational outputs into usable data products that can be reliably found, assembled, interpreted, and reused by laboratory, project management, Computational Immunology, and Data Platform teams.

The work includes metadata systems, lineage and provenance capture, dataset contracts, FAIR data practices, data catalog capabilities, and semantic integration between pipelines, datasets, and scientific outputs.

This is a hands-on engineering role for someone who enjoys working across platform engineering, scientific workflows, metadata systems, and cloud-native infrastructure, while staying grounded in practical delivery and operational ownership.

The role is hybrid, with an expectation of working from our London office a couple of days per week.

TEAM AND WAYS OF WORKING

You will join a small, growing Data Platform function working closely with Computational Immunology, wet lab, and clinical-facing teams.

This role sits within the platform layer: helping build the shared foundations that allow teams to ingest, structure, govern, discover, process, assemble, and reuse scientific data reliably.

You will not be working in isolation. The role is deeply connected to the wider platform effort and will involve close collaboration with engineers responsible for ingestion, orchestration, infrastructure, security, transformation, and platform operations.

As a senior engineer, you will be expected to:

- Own substantial technical problems from discovery through implementation and operation.

- Work directly with stakeholders to gather requirements and translate them into practical platform capabilities.

- Influence platform architecture and engineering standards alongside the wider Data Platform team.

- Make pragmatic technical trade-offs in environments with evolving scientific and operational requirements.

- Contribute to shaping how the platform evolves as usage, scale, and regulatory expectations grow.

You should be comfortable balancing hands-on implementation work with technical leadership, collaboration, and operational ownership.

WHAT YOU WILL DO

- Build and maintain metadata, semantic, lineage, and provenance capabilities within the core Data Platform.

- Work closely with the Computational Immunology team to understand analytical workflows and translate them into dataset contracts, metadata standards, and reusable platform capabilities.

- Develop systems for structuring, validating, registering, versioning, and governing scientific datasets and computational outputs.

- Build ingestion pathways that return outputs from analytical and machine learning pipelines to the Data Platform as governed and reusable scientific datasets.

- Help establish practical patterns for discovering, assembling, and delivering trusted datasets to laboratory, Computational Immunology, and operational teams.

- Improve data discoverability, usability, lineage, provenance, auditability, reproducibility, and reuse through well-structured, named, versioned, archived, and analysis-ready data products aligned with practical FAIR data principles.

- Contribute to data catalog and scientific knowledge graph capabilities that connect datasets, workflows, biological entities, analytical outputs, and scientific conclusions.

- Build AWS-native services, APIs, automation, and platform tooling using modern engineering practices.

- Work closely with scientists, computational immunologists, software engineers, and platform users to turn real scientific and data problems into reliable platform capabilities.

- Improve observability, reliability, documentation, maintainability, and operational maturity across semantic and metadata services.

WHAT WE ARE LOOKING FOR

CORE EXPERIENCE

We do not expect every candidate to have used every technology in our stack. We are mainly looking for strong engineering judgement, practical delivery experience, and evidence of building reliable systems in complex data environments.

- Strong software engineering experience in Python.

- Practical experience building and operating cloud-native systems on AWS.

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