Lab Platform Technical Lead

Job Description

We run the enterprise SaaS platforms, APIs, and data integrations that our research organisation depends on every day. You will be the technical owner of one of them: the Signals Research Suite — the electronic lab notebook platform used by scientists across several divisions worldwide.

This is a hands-on configuration, integration, and platform engineering role, not a ticket queue. You will own the technical roadmap, run the release pipeline, drive the vendor feature backlog, automate the manual work away, and decide where the platform goes next.

Our platform happens to serve laboratory and experiment-management workflows, so you will learn that domain here — and you will learn Signals itself here. We do not expect you to arrive with either. What we do expect is that you have owned a production platform before and know how to make one better.

Reports to the Product Technical Lead.

What You Will Do

Own the platform

Act as technical owner for the Signals Research Suite and the integrations around it

Own the configuration, customisation, and development of the suite's modules to meet evolving research and business needs

Translate scientific workflow requirements into platform configuration (templates, experiments, workflows, ADTs) and into integrations with other systems

Own and prioritise the enhancement backlog, and contribute to the target-state architecture and technical roadmap for the platform

Run releases and production

Manage the full SDLC: requirement gathering and analysis, solution design and configuration, development and scripting, collaboration with testing and UAT teams, deployment via the Configuration Transfer Tool or equivalent, production release, and hypercare

Lead investigation and resolution of production incidents across application, API, data, identity, and network layers

Drive structured root-cause analysis and corrective actions to closure; improve monitoring, alerting, runbooks, and operational metrics so the next incident is shorter — or does not happen

Apply ITSM practices across Incident, Request, Problem, Change, Knowledge, and Release Management

Engineer and integrate

Build and maintain integrations between Signals, internal enterprise services, SaaS and cloud applications, and legacy systems, using APIs and middleware

Debug data-consistency and integration failures across APIs, event flows, and identity boundaries

Use cloud services and enterprise networking knowledge to diagnose and harden platform reliability

Support deployments, go-live readiness, rollback planning, and post-deployment stabilisation

Automate and use AI well

Automate repetitive operational work — triage, configuration comparison, checks, reporting, provisioning — with scripting and approved tooling

Drive AI initiatives that enhance scientific workflows for business users

Build internal AI-powered tools (e.g. a technical RAG chatbot) that accelerate team onboarding, troubleshooting, and self-service how-to guidance

Use AI-assisted tooling for log analysis, incident triage, investigation, and knowledge capture — and validate its output against real platform evidence before acting on it

Set technical direction

Serve as technical liaison with Revvity (the vendor) for escalations, defects, feature requests, enhancements, upgrades, and release coordination

Prioritise technical work with the Product Owner, and communicate risk, impact, and options to technical and non-technical audiences alike

Collaborate with cross-functional teams including Product Owner, Product Technical Lead, Quality Unit, infrastructure, and support

Mentor less experienced engineers and contribute to engineering standards and documentation

Work in a global, distributed Agile team following product model practices

Work in a regulated environment

Follow established validation, change-control, and documentation practices — our platforms are audit-sensitive, and we will train you on what that means in practice

Document configurations, processes, and troubleshooting guides to support knowledge sharing and compliance requirements

Identify security, access, and data-protection risks early and bring in security and architecture partners

What You Bring

4+ years engineering, operating, configuring, or owning production software platforms, SaaS solutions, or enterprise systems

Real production incident experience: you have been on the sharp end of an outage, led the investigation, and closed the loop afterwards

Strong understanding of the complete SDLC, from requirements through production release and hypercare

Solid debugging skills across the stack — application, API, data, identity, and network — with a structured approach to root-cause analysis

Working knowledge of a major cloud platform (AWS, Azure, or GCP) and of enterprise networking fundamentals (DNS, TLS, firewalls, proxies, connectivity patterns)

Scripting or development ability (Python or similar) for automation, and working knowledge of API and integration patterns, including RESTful services

Practical use of AI-assisted tools in engineering or operations work, with sound judgement about their output

Self-driven and proactive: demonstrated ability to identify opportunities, propose solutions, and execute independently rather than waiting to be asked

Clear written and spoken English, and the ability to work with distributed teams across Europe, the US, and India

Bachelor's degree in Computer Science, Engineering, Information Systems, or a life sciences field (biology, chemistry, biotechnology, bioinformatics, biomedical engineering, or similar) — or equivalent practical experience. We welcome scientists who moved into engineering

Nice to Have (Not Required)

We will teach you the platform and the domain. Any of the following is a bonus, none is a filter:

Experience with an ELN or LIMS platform, and in particular the Signals One Research Suite and its modules (Notebook, VitroVivo, Inventa, CD, Synergy) or the Signals Notebook REST API

Other scientific informatics platforms — LIMS, ELN, sample management — or specific products such as Benchling or ZONTAL

Familiarity with scientific data standards (SDF, HELM, chemical structures) or with laboratory workflows such as stoichiometry, assay data, or sample management

Observability tooling (Dynatrace, Grafana, Datadog, Splunk, CloudWatch or similar)

Infrastructure as code, CI/CD pipelines (GitHub, GitHub Actions), or containers

Additional languages and libraries: SQL, C#, PowerShell, Bash, Pandas, Streamlit

Experience in a regulated, GxP, or otherwise audit-sensitive environment, including 21 CFR Part 11 / Annex 11

Experience with AI/LLM technologies, RAG architectures, or building AI-powered internal tools

Experience with Agile/Scrum delivery; ITIL v4 Foundation, Six Sigma Green Belt, or similar certification

Life sciences, pharma, research, or manufacturing IT background

Advanced degree

What Success Looks Like

In the first 6 months you will:

Co-deliver 2 Signals software releases to production alongside the existing team

Map current configuration, validation, and deployment processes end to end and identify improvement opportunities across them

Own and prioritise the Signals enhancement backlog, aligning vendor feature requests with business needs and release timelines

Establish yourself as the primary technical liaison with Revvity for feature coordination, escalations, and release planning

In the first 12 months you will:

Deliver Signals software releases to production independently

Drive 2-3 vendor feature enhancements from requirement through production release, coordinating across Revvity, QA, and business stakeholders

Implement automated configuration promotion, reducing manual effort and deployment risk

Build and maintain a living enhancement roadmap that gives the Product Technical Lead and