R&D Technical Analyst / Researcher in Peterlee

We're building out a dedicated R&D capability to systematically explore emerging technologies, validate new approaches, and feed innovation into our product and engineering teams. This role is central to making that work. As our R&D Technical Analyst, you drive evidence generation through our stage gates: Problem Pack support, vendor/option evaluation, Evidence Pack drafting, decision logging, and handover pack creation. Your activities include scanning the market for emerging tools and vendors, conducting technical research and ensuring that ideas move through our process with the right evidence and documentation behind them.

Contribute code to timeboxed PoCs under the Senior R&D Engineer’s technical direction; focus is validation and evidence, not production-grade implementation. You'll work closely with our architecture team, freeing them to focus on high-value design decisions while you handle the groundwork: gathering technical specs, evaluating options, and preparing the analysis that supports good decision-making. You'll also support our Senior R&D Engineer during prototyping phases, contributing hands-on work while ensuring findings are captured and communicated clearly. AI and process automation are core focus areas for our R&D efforts. You'll need a solid grasp of the current AI landscape; what's hype, what's production-ready, and where the genuine opportunities lie; alongside an interest in how organisations orchestrate and automate complex business processes.

Functionally reporting to Head of R&D your day to day tasking and coaching is from the Senior R&D Engineer. This is a role with real growth potential. For the right person, it's a launchpad into more senior R&D engineering or specialist AI/data roles as our capability matures.

What You’ll Do

• Research & Analysis

• Scan the market for emerging technologies, tools, platforms, and vendors relevant to our strategic priorities.
• Conduct structured evaluations: gathering documentation, assessing technical fit, comparing options, and summarising findings for decision-makers.
• Assess vendor and platform security posture, including availability of SAST, DAST, IAST, RASP capabilities, secure SDLC alignment, and compliance certifications.
• Stay current with developments in AI/ML, understanding the practical applications and limitations of new models, frameworks, and services.
• Prepare evidence packs and recommendations to support architecture and strategy fit assessments.
• Research and evaluate process automation and orchestration technologies, including workflow engines, BPMN platforms, RPA tools, and the emerging BOAT (Business Orchestration and Automation Technologies) landscape.
• Apply a consistent evaluation rubric (fit, integration complexity, security/compliance, operating cost, adoption maturity, vendor viability) for vendor selection.

• Build small proofs of concept to test APIs, integration approaches, and technical hypotheses.
• Support the Senior R&D Engineer during prototyping, contributing code and technical investigation under their guidance.
• Work with C# and Python to create lightweight demonstrations and validate technical assumptions.
• Explore all capabilities practically: testing APIs, evaluating model performance, building simple AI-integrated applications.

• Own the documentation of R&D activities: hypotheses, findings, decisions, and outcomes.
• Produce decision-ready 1–2 page summaries: options, evaluation criteria, risks, costs, recommendation, and confidence level.
• Maintain our knowledge base of evaluated technologies, lessons learned, and archived initiatives.
• Communicate progress and findings to architecture, product, and development teams.

• Maintain the R&D backlog; enforce stage gate completion; track decisions (pass/revise/stop) and rationale; maintain archive of stopped initiatives.
• Keep our process running smoothly, flagging blockers and ensuring nothing falls through the cracks.
• Maintain the archive of completed and rejected initiatives for future reference.
• Owning roadmaps.
• Shipping BAU features.
• Acting as a sprint delivery resource.
• BAU support.

What You’ll Bring

• At least two years’ demonstrable experience in a technical analyst, solutions analyst, technical research, or similar role.
• Hands-on coding ability in Python and/or C#: you don't need to be a full-stack developer, but you can write functional code to test an idea.
• A solid understanding of the current AI/ML landscape: large language models, AI APIs and services, practical applications, and realistic limitations.
• Strong analytical skills and a structured approach to research and evaluation.
• Excellent documentation and technical writing ability: you can synthesise complex findings into clear recommendations.
• Operate with strong stakeholder management: chase inputs, enforce gate evidence standards, and surface blockers early.
• Self-directed: you can take an open brief and return with structured, actionable findings.
• Familiarity with process automation concepts; you don't need to be an expert, but you understand workflow orchestration, BPMN basics, and why organisations automate processes.
• Experience building AI-integrated applications (working with OpenAI, Azure AI, AWS AI services, or similar).
• Familiarity with API integration, cloud platforms, and modern software architecture concepts.
• Experience with vendor evaluation, procurement support, or technology selection processes.
• Understanding of software development lifecycles and delivery practices.
• Exposure to process orchestration platforms (Camunda, Temporal, or similar) or business automation tools.
• Understanding of BPMN notation and process modelling.
• Degree in a technical discipline (Computer Science, Software Engineering, or similar) though equivalent practical experience is equally valued.

How You’ll Work

You’ll report directly to Senior R&D Engineer and work day-to-day with:

• Architecture team - providing research support, preparing assessments, and freeing them to focus on design decisions.
• Senior R&D Engineer - supporting prototyping work, contributing code, and documenting findings.
• Product team - gathering context on strategic fit and roadmap alignment.
• Development teams - preparing handover materials and bridging exploratory work with operational delivery.

You’ll spend significant time working independently; researching, analysing, documenting; punctuated by collaborative sessions where your findings inform team decisions.

How success is measured

• Quality and clarity of research and evidence produced.
• Speed and discipline in moving initiatives through R&D gates.
• Contribution to successful transitions into delivery teams.
• Adoption of R&D outputs by Engineering and Product.

What success looks like in your first 90 days

• Established or contribute to the R&D backlog and knowledge base.
• Contributed to 2–3 evidence packs for live initiatives.
• Helped standardise R&D gate artefacts and evaluation templates.
• Supported at least one initiative through to a handover-ready recommendation.

What’s In It for You

• A genuine opportunity to shape how we approach innovation and emerging technology.
• Exposure to cutting-edge AI and technology trends as a core part of your role.
• A clear growth path into more senior R&D, AI engineering, or specialist technical roles.
• Direct access to senior leadership and influence over strategic technology decisions.

A Few Things to Note

We're looking for curiosity and rigour in equal measure. The right person is genuinely excited by emerging technology, particularly AI, but also disciplined enough to separate signal from noise and present balanced, evidence-based recommendations. You don't need to be an expert in everything. But you should be comfortable operating at the boundary of your knowledge, learning quickly, and asking good questions.