About K3 Advisory Group

K3 Advisory Group is a UK professional services group with 18 trading subsidiaries and more than 1,200 staff. The Group spans corporate finance, tax, restructuring and insolvency, legal, financial planning, and technology-enabled advisory services.

All technology delivery must balance the pace required to exploit AI, data and automation with strict expectations around governance, regulatory obligations, security-by-design, audit trails, and client confidentiality.

Group Technology builds shared platforms, data foundations and AI-assisted products that scale across these businesses while accommodating local variation. Engineers in this team work close to commercial outcomes, with direct visibility of advisors, partners and clients.

Role Purpose

Build secure, reliable web applications, APIs and integration layers that turn K3's existing data and analytics platforms into governed, user-facing products. The role sits at the point where complex internal data, embedded analytics and AI-assisted features are packaged into product experiences that advisors, partners and clients can use safely and confidently.

The successful engineer treats access control, tenancy and auditability as first-class product features — not afterthoughts — and is comfortable making pragmatic trade-offs between speed of delivery and the controls expected in a professional services environment.

Key Responsibilities

Product Engineering

Build full-stack product features using .NET, TypeScript, React/Next.js and backend API services.
Translate product, design and analytics requirements into well-structured front-end components and resilient backend services.
Develop API endpoints supporting dashboards, exports, administration and AI-assisted product features.
Integrate embedded analytics, reporting views and export workflows including PDF, Excel and presentation-ready outputs suitable for client delivery.

Security, Identity & Access

Implement secure authentication, authorisation, user/client access models and role-based permissions.
Build server-side routing patterns that ensure users only access the data, dashboards and tools they are authorised to use.
Apply tenant isolation patterns so that data belonging to one client or subsidiary cannot leak into another, by design and not by convention.
Implement audit logging for login events, access changes, data requests, exports and support actions.

Quality, Testing & Operability

Write automated tests for tenancy, permissions, denial paths and critical user journeys — not just happy-path scenarios.
Contribute to CI/CD pipelines, observability (logs, metrics, traces) and runbook documentation for the services they own.
Participate in code review and design review, raising the engineering quality bar across the team.

Collaboration

Work with data engineers and AI engineers to expose safe, read-only data and AI capabilities inside product workflows.
Work with product, design and business stakeholders to understand how advisors and clients actually use the features being built.
Contribute to technical design documents, implementation notes and operational runbooks.

Required Experience & Skills

4+ years building production web applications and APIs.
Strong TypeScript, React or Next.js experience, with sound understanding of component design, accessibility and performance.
Backend experience with Node.js, .NET or a similar service framework.
Experience with Auth0, Microsoft Entra ID, Azure AD B2C or a similar identity platform.
Experience designing permission models, access grants or multi-tenant application patterns.
SQL fluency and API integration experience across REST and, ideally, GraphQL or event-driven patterns.
CI/CD, automated testing, observability and secure coding practices as part of normal day-to-day delivery.
Comfortable working with product, data and security stakeholders, and able to explain technical trade-offs in plain language.

Desirable Experience

Exposure to regulated environments — financial services, professional services, healthcare or legal — where audit trails and access control are scrutinised.
Experience integrating with finance, CRM, practice management or case management systems.
Familiarity with Azure cloud services, infrastructure-as-code (Terraform) and platform engineering practices.
Exposure to AI-assisted features, including embedding LLM-driven capabilities into user-facing applications.

Success Measures

Delivery quality: Product features delivered with clear access control, meaningful test coverage and low production defect rates.
Operability: Core user journeys meet agreed performance, availability and auditability expectations.
Leverage: Manual setup and support steps reduce over time as controlled admin tooling matures.

Working Environment

Reporting line: Group Technology leadership, working day-to-day within a cross-functional product squad (engineering, data, AI, design, product).
Stakeholders: UK-based business leaders, partners, operational teams, compliance and risk functions, and client-facing advisors across multiple subsidiaries.
Delivery model: Iterative, product-led delivery with short feedback loops, paired with the governance discipline appropriate to a regulated professional services environment.
Tooling baseline: Modern cloud platform (Azure-first), Git-based source control, CI/CD pipelines, infrastructure-as-code, observability tooling and a documented engineering handbook.
Ways of working: Code review, pairing, design reviews, threat modelling for sensitive features, and lightweight architecture decision records (ADRs).

Governance, Security & Compliance Expectations

Every engineer in Group Technology is expected to treat the following as non-negotiable foundations, not optional extras:

Confidentiality: Client, matter, and case data is highly sensitive. Need-to-know access is the default; broad access is the exception and must be justified.
Security by design: Threat modelling, secure defaults, secrets management, dependency scanning and least-privilege access are built into features from day one.
Auditability: User actions, data access and administrative changes are logged in a tamper-evident, queryable form suitable for internal audit and regulatory review.
Responsible AI: Where AI is used, model behaviour, prompts, tools and data access are versioned, evaluated and monitored. Human oversight is preserved for material decisions.
Regulatory awareness: For features touching FCA-regulated entities (e.g. Pareto, Luna), additional controls apply around record-keeping, client communications and data handling. Engineers are expected to flag uncertainty early.
Data protection: UK GDPR and Group data protection standards apply across all subsidiaries; data minimisation, lawful basis and retention controls are part of normal design.

Development & Progression

Clear engineering career path with senior, lead and principal levels, plus a parallel route into architecture or engineering management.
Exposure to acquisitions, integrations and greenfield product builds across multiple professional services disciplines.
Supported learning budget, certifications relevant to the role, and time allocated for proof-of-concept work and tooling improvements.
Direct line of sight to commercial outcomes — engineers see how their work changes how advisors and clients actually operate.

Person Specification

Pragmatic: Knows when to use a proven pattern and when bespoke engineering is justified.
Security-minded: Treats access control, secrets handling and audit as design inputs rather than late additions.
Commercially aware: Understands that delivery speed matters, and balances that against the controls a regulated, multi-entity Group requires.
Collaborative: Works well across engineering, data, AI, product and business stakeholders without needing constant translation.
Curious: Comfortable digging into unfamiliar data, systems or domains acquired through the Group's ongoing M&A activity.

Fullstack Software Engineer

Fullstack Software Engineer - Hybrid