Senior Engineer - Agentic Systems

Next 15 Group Plc; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

25 days leave

Life assurance

Healthcare plan

Cycle to work

Job summary

Next 15 Group plc is seeking a Senior Engineer for its Agentic Systems squad based in the UK. The role is fully remote across the UK with travel to London about once per month.

You’ll shape, build and operate an early-stage platform, taking ownership from shaping to production and mentoring other engineers. We expect you to turn ambitious visions into practical technical direction, make trade-offs, and deliver focused vertical slices that create real business value while maintaining security,

Qualifications

• Strong experience building production-grade software with TypeScript and Node.js.
• Proven ability to own ambiguous, greenfield initiatives from shaping to production.
• Experience designing and consuming third-party API integrations.
• Familiarity with authentication, permissions, identity and secure data handling.
• Mentoring or leading engineers in a product development environment.

Responsibilities

• Turn vision into practical technical direction in a greenfield setting.
• Own substantial parts of the platform from early shaping to production.
• Lead architectural decisions and trade-offs with partial information.
• Design secure, observable, and maintainable systems.
• Build production-grade TypeScript/Node.js services and integrations.
• Mentor other engineers and establish team practices.
• Collaborate with product to identify workflows worth solving.
• Deliver narrow, testable vertical slices creating real business value.
• Ensure tracing, logging and auditability.

Skills

TypeScript

Node.js

Production software

APIs & integrations

Mentoring engineers

Greenfield projects

Tools

LLM APIs

Tool call frameworks

Retrieval systems

Job description

Senior Engineer - Agentic Systems Next 15 Group plc London, England, United Kingdom

Building the Intelligence Layer for How Pretzl Works

Pretzl is redefining what a B2B marketing agency can be. As a B2B Technology-and-People-as-a-Service (TaPaaS) agency with approx. 350 people globally, we're not just advising clients - we're building the technology that transforms how businesses connect with their buyers.

We are now creating an Agentic Layer across the business: a platform that can safely connect AI systems with the context, tools, knowledge and workflows people need to do useful work.

The Role

We’re looking for a Senior Engineer to join our newly forming Agentic Systems squad and help us shape, build and operate this platform from the ground up.

This is an early-stage, greenfield engineering opportunity. You will join while the first use cases, architectural hypotheses and prototypes are being explored, but before the production architecture, delivery model and technical boundaries have been settled.

You’ll need to be confident operating in that environment: turning an ambitious vision into a practical technical direction, making sensible decisions with incomplete information, identifying what needs to be learned first, and delivering narrow working slices rather than waiting for every future requirement to be resolved.

This isn’t a role for someone who wants to be handed fully specified tickets and churn out code. We need someone who wants to get involved while problems are still being clarified, workflows are being understood, trade-offs are being discussed, and the right platform shape is still emerging.

You’ll be the first fully allocated technical contributor within a new team that will grow with you to up to 3 fully allocated engineers, as well as additional resource pulled in from other pods. You’ll own substantial parts of the platform from early shaping through to production, help establish its technical foundations, contribute strongly to architectural direction, mentor other engineers, and raise the standard for how the team plans, builds, reviews and operates its work.

You will not be expected to arrive with every answer. You will be expected to create clarity, make good decisions, test assumptions quickly, and take meaningful ownership rather than waiting for somebody else to define the path.

This is a fully remote, UK-based role with the expectation to travel to London approximately once per month. We are not currently hiring this role as an overseas remote position.

What We’re Building

The Agentic Layer will give AI agents and automation workflows safe, useful context about how Pretzl operates: who people are, which clients and projects matter, what work is in flight, what has already been agreed, what has changed, and which information can appropriately be used for a particular task.

This is not a generic chatbot, a thin wrapper around an LLM, or simply a vector database connected to company documents.

The platform needs to understand business entities, relationships, ownership, permissions, project state, decisions, risks, workflows and source systems. It must be able to load the right context for a task without exposing information the user is not entitled to access.

We expect to use external models, frameworks, connectors and infrastructure where that makes sense. The capabilities we need to own are the parts that are specific to how Pretzl works: our context and memory models, permission boundaries, business events, source-of-truth decisions, evaluation criteria and rules around how agents can use information and take action.

The first version will not attempt to create a universal agent for the whole business. We will begin with a small number of valuable, clearly defined workflows where we can understand the users, context, systems, permissions, approval points and measures of success.

What You’ll Actually Do

Greenfield Technical Ownership

Help turn the Agentic Layer vision into a practical, evolvable technical direction

Own substantial areas of the platform from early shaping through to production operation

Identify the important architectural decisions, assumptions, risks and unknowns rather than waiting for them to be surfaced by somebody else

Work out what needs to be built now, what can be deferred, and what should be bought, reused or integrated

Establish sensible technical foundations without over-engineering a platform before its first workflows have proved value

Turn broad platform ambitions into narrow, testable vertical slices that create real business value

Make architectural decisions within your domain and clearly articulate the trade-offs

Design systems that are secure, observable, testable, maintainable and appropriately scalable

Lead debugging and incident investigation for complex issues, looking for systemic causes rather than treating symptoms

Write code that serves as an example for the rest of the team

Agentic Systems, Context and Integrations

Build production-grade TypeScript and Node.js services, APIs and internal tools

Design context-loading approaches that identify what an agent needs to know for a specific user, client, project or workflow

Help shape models for business entities, events, decisions, risks, workflows and durable memory

Build permission-aware access across connected systems and document repositories

Create reliable integrations with workplace and business platforms such as Slack, Microsoft Graph, SharePoint, OneDrive, Outlook, Teams, Snowflake, Jira, Figma and internal systems

Design agent workflows that can call approved tools, maintain state, handle failures and pause for human approval where required

Apply agentic patterns such as tool calling, structured outputs, retrieval, Model Context Protocol and human-in-the-loop workflows pragmatically

Build clear boundaries around tool access, credentials, identity, sensitive data and external actions

Establish tracing, logging and auditability so that we can understand what an agent saw, why it acted, which tools it used and what happened

Build evaluation and feedback mechanisms that help us identify missing context, weak outputs, unsafe behaviour and genuinely valuable workflows

Protect the platform against risks including permission leakage, prompt injection, stale context, unintended data disclosure and uncontrolled tool execution

Product and Workflow Collaboration

Work directly with product leadership, stakeholders and your squad to identify workflows worth solving

Get close to how teams currently work rather than designing a platform around abstract AI capabilities

Help turn ambiguous operational problems into clear technical approaches and sensible delivery plans

Challenge unclear assumptions and proposed solutions constructively

Help identify which systems should be treated as sources of truth for different types of business information

Clarify gaps, dependencies, permission boundaries and operational risks before they become delivery blockers

Communicate technical concepts and trade-offs clearly to technical and non-technical stakeholders

Distinguish between an impressive demonstration and a workflow that will remain reliable in real business use

Proactively identify and raise risks before they become critical

Delivery Quality

Own delivery quality as well as implementation

Break larger platform opportunities into small, reviewable, outcome-connected pieces of work

Create clear technical plans and pull requests that explain the reasoning behind the implementation, not just the code changes

Ensure work is meaningfully tested and production-ready

Design for unreliable APIs, asynchronous processing, partial failure, retries and changing external systems

Build appropriate observability and operational controls into the work rather than adding them afterwards

Keep changes focused, understandable and maintainable

Surface uncertainty early rather than allowing unclear work to drift into delivery

Use AI development tools thoughtfully, treating tools such as Cursor, Claude Code and Codex as collaborators that help explore and challenge solutions, not shortcuts that bypass understanding

Team Development

Actively mentor and collaborate with other engineers through pairing, design discussions, code reviews and feedback

Help other engineers develop stronger architectural and product judgement, not just stronger technical execution

Create opportunities for others to take ownership and stretch their capabilities

Champion engineering practices that improve clarity, quality, security and pace

Help establish the working practices of a newly forming team

Contribute to hiring and onboarding activities

What We’re Looking For

We’re looking for a strong Senior Engineer who is excited by the opportunity to build an AI-enabled internal platform from the ground up.

You do not need to be a machine learning researcher. This role is primarily about building secure, reliable production software around models: integrations, context, permissions, workflows, tools, data, evaluation and operational controls.

You should be comfortable taking ownership in an environment where the destination is clear but the route still needs to be worked out.

A sustained track record of operating effectively at Senior Engineer level; this is not intended as a first Senior Engineer appointment

Strong professional experience building production software with TypeScript and Node.js

Proven ownership of complex, ambiguous or business-critical initiatives from early shaping through to production

Confidence joining a greenfield project and helping establish its architecture, technical standards and delivery approach

Ability to create clarity from ambiguity, make pragmatic decisions and move work forward without waiting for complete specifications

Strong experience designing, consuming and maintaining third-party API integrations

Good understanding of authentication, authorisation, permissions models, identity and secure data handling

Experience with databases, queues, background jobs, events, webhooks or other asynchronous system patterns

Practical experience building with LLM APIs, tool calling, agent workflows, retrieval systems or AI-enabled software

Ability to design systems that handle sensitive business data with appropriate access control, auditability, observability and human oversight

Strong product engineering judgement, including the ability to turn broad operational problems into simple, reliable software

A pragmatic approach to architecture, testing, maintainability, technical debt and operational risk

Excellent communication skills, with the ability to explain technical decisions and trade-offs to technical and non-technical colleagues

A track record of mentoring other engineers and raising the quality of the wider team

Curiosity about what AI can genuinely improve, combined with healthy scepticism around reliability, privacy, security and hype

Nice to Have

Experience in one or more of the following areas would be particularly useful:

Building MCP servers, MCP clients, tool registries or secure agent-accessible APIs

Slack, Microsoft Graph, SharePoint, OneDrive, Outlook, Teams, Google Workspace, Jira, Snowflake, Figma or similar workplace and business-system APIs

Permission-aware retrieval, semantic search, embeddings, vector databases, knowledge graphs, document indexing or source-attributed answer generation

Agent SDKs, workflow frameworks or application libraries such as the OpenAI Agents SDK, Anthropic tooling, LangGraph, Vercel AI SDK or equivalent approaches

Agent harnesses or coding-agent environments such as Claude Code, Codex, Pi, OpenHands or similar systems

Evaluation frameworks, tracing, red-teaming, AI security testing or observability for nondeterministic systems

Designing secure access across multiple clients, business units, teams or document repositories

Building internal platforms, workflow automation products or operational intelligence systems

You do not need experience with every item in this list. We care more about whether you understand the underlying engineering problems and can make good decisions as the technology continues to change.

Deal-breakers

If you’re looking for a role where the platform has already been designed and you only need to implement tickets, this isn’t for you

If you’re primarily interested in prototypes and impressive demonstrations rather than reliable production systems, this isn’t for you

If you believe connecting an LLM to a collection of documents is the complete architecture, this isn’t for you

If you are comfortable giving agents broad access to tools or company data without clear permission boundaries, auditability and human control, this isn’t for you

If you use AI tools to generate systems you cannot explain, debug or maintain, this isn’t for you

Our Likely Starting Stack

Some decisions will be made with the engineers joining the team, but our expected starting point is:

Data: PostgreSQL, Snowflake and appropriate retrieval or indexing infrastructure

Integrations: Slack, Microsoft Graph, SharePoint, OneDrive and other business-system APIs

Agentic capabilities: LLM APIs, typed tool interfaces, MCP and workflow or agent SDKs selected according to the problem

Operations: Structured logging, tracing, evaluation, audit history and production monitoring

We expect the team to make deliberate choices rather than adopting frameworks for their own sake. TypeScript and Node.js are the default because they fit our existing engineering organisation and make the platform easier for other Pretzl engineers to understand, review and contribute to.

If a genuine architectural reason emerges to use another technology for part of the platform, we are open to that decision being made consciously by the team.

Compensation and Benefits

What You’ll Get

Competitive compensation package

25 days leave, increasing to 30 days based on service

Additional “moments that matter” days for birthdays, sports days and other important life moments

Time off for volunteering

Life assurance, healthcare cash plan, employee assistance programme and Digital GP

Cycle to work scheme

Flexible spending allowance for health and dental insurance, wellbeing, family life, work life, hobbies and experiences

Quarterly in-person and virtual social activities

Office transfer and secondment opportunities

Location: Fully remote across the UK, with travel to London approximately once per month.

Interested?

If you’re an experienced Senior Engineer who wants to take real ownership of a greenfield platform, solve difficult problems around context, permissions, integrations and agentic workflows, and help establish how a new team operates, we’d love to hear from you.

Apply now or reach out to learn more about Pretzl and the Agentic Systems team.

Pretzl believes that a diverse workforce is not just a social good, but a commercial advantage. We're committed to ensuring our people are treated equally regardless of culture, gender and non-binary identity, sexual orientation, ethnicity, religious beliefs, diversity of thought, skills, marital status, family composition, education, age, disability or any other characteristic.

This diversity of backgrounds, knowledge and experience helps us do the best work for our clients and continue to attract the best people. We encourage applications from candidates of all backgrounds.

Full-time