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Whitespace Careers

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At Whitespace, we build intelligent systems that people can trust- AI and digital platforms that power defence, government, and leading commercial organisations. Our work sits at the edge of what’s possible, where technology meets security and real-world impact.
<br><br>We’re engineers, designers, and problem-solvers who care about clarity, precision, and purpose. Our teams create technology that helps national programmes run smarter and global businesses act faster.

We move quickly, cut through noise, and give talented people the space to build things that matter. <br><br>Whether it’s a secure AI platform for government or automation for a global enterprise, the challenge is the same: make complex systems simple, reliable, and human to use.<br><br>If you want your work to count - join us.

Why We're Here

<html><head></head><body><div>
<div><strong>Department: Engineering</strong></div>
<div><strong>Hours: Full-time</strong></div>
<div><strong>Reporting to: Head of Solutions Engineering</strong></div>
<div><strong>Salary: £70,000 - £85,000 p.a. (+EMI share options)</strong></div>
<div>&nbsp;</div>
<h2><br><strong>About Whitespace</strong></h2>
<p>Whitespace leads in creating smarter, safer AI solutions for enterprises. As AI presents transformative opportunities, many companies struggle to harness its full potential.</p>
<div>Whitespace bridges this gap with Collective - The AI Operating System for high-assurance environments. Built for scale, trust and action - even in the most secure, complex or disconnected settings.</div>
<div>&nbsp;</div>
<div>We're not just building AI systems. We're laying the foundation for a future where humans and machines work together like never before.</div>
<h2><br><strong>Role Summary</strong></h2>
<div>The successful AI Solutions Engineer will extend and enhance our AI Operating System, which leverages LLMs to solve industry-specific challenges across defence, legal, health, infrastructure and management consulting sectors.</div>
<div>&nbsp;</div>
<div>This is a hands-on lead role focused on rapidly prototyping and deploying AI-powered solutions. Working directly with clients, you will translate their needs into scalable, production-ready AI applications using modern frameworks and techniques.</div>
<h2><br><strong>Duties &amp; Responsibilities</strong></h2>
<h2><strong>Technical Development</strong></h2>
<ul>
<li>Develop platform functionality using Python, building APIs and integrations to extend capabilities for diverse client needs.</li>
<li>Design and implement LLM-powered applications and workflows using open source models such as Llama, Qwen and Gemma, as well as those online models from OpenAI, Gemini, etc.</li>
<li>Build AI agents with tool/function calling, prompt engineering and appropriate guardrails using frameworks such as OpenAI AgentSDK, LangGraph or LlamaIndex.</li>
<li>Implement testing and evaluation frameworks for LLM applications, covering prompt testing, output quality metrics and agent behaviour validation.</li>
<li>Apply relevant AI technologies as needed, including retrieval systems (RAG, GraphRAG), knowledge graphs, vector databases or data pipelines.</li>
</ul>
<div>&nbsp;</div>
<h3><strong>Solution Design and Implementation</strong></h3>
<ul>
<li>Design and deliver scalable, efficient solutions tailored to client-specific requirements whilst balancing innovation with practical constraints around compliance, performance, cost and security.</li>
<li>Lead technical discussions, diagnose complex challenges and provide guidance to less experienced team members.</li>
</ul>
<div>&nbsp;</div>
<h3><strong>Client Engagement and Collaboration</strong></h3>
<ul>
<li>Work directly with clients to gather requirements and translate them into actionable AI-powered solutions, moving rapidly from concept to working prototype.</li>
<li>Communicate complex technical concepts effectively to technical and non-technical stakeholders, including system capabilities and limitations.</li>
<li>Mentor junior engineers and contribute to technical knowledge sharing within the team.</li>
</ul>
<div>&nbsp;</div>
<h2><strong>Role Requirements</strong></h2>
<h3><strong>Work Experience</strong></h3>
<ul>
<li>At least five years as a software engineer on commercial platforms, with demonstrable experience building production LLM-powered applications.</li>
<li>Proven experience with API-level LLM usage, including tool/function calling, prompt engineering and evaluation.</li>
<li>Experience with agent frameworks (OpenAI AgentSDK, LangGraph, LlamaIndex Agents or similar).</li>
<li>Experience developing APIs using FastAPI or similar frameworks and integrating with third-party platforms.</li>
<li>Direct client-facing experience gathering requirements and delivering technical implementations.</li>
<li>Experience within agile development workflows and engineering teams.</li>
</ul>
<div>&nbsp;</div>
<h3><strong>Skills &amp; Abilities</strong></h3>
<ul>
<li>Strong Python (or similar) programming skills with a focus on production-grade applications.</li>
<li>Excellent communication abilities, translating complex technical concepts for diverse audiences.</li>
<li>Strong analytical and problem-solving approach, identifying scalable and reusable solutions.</li>
<li>Leadership qualities, including technical mentorship, team collaboration and line management.</li>
<li>Ability to align solutions with business goals and industry-specific constraints.</li>
<li>Self-sufficient contributor capable of working independently and seeking support when needed.</li>
</ul>
<div>&nbsp;</div>
<div><strong>Nice to Have</strong></div>
<div>&nbsp;</div>
<div><br>The following are examples of specialised areas that would be valuable. Deep expertise in some of these areas is preferred over surface-level knowledge across all domains.</div>
<div>&nbsp;</div>
<ul>
<li>Open source LLMs (Llama, Qwen, Gemma, GPT OSS) and local deployment strategies.</li>
<li>Frameworks and protocols such as Model Context Protocol (MCP) or Agent-to-Agent (A2A).</li>
<li>LLM evaluation tooling (OpenAI Evals, LangSmith, custom evaluation harnesses).</li>
<li>Advanced agent patterns: multi-agent systems, supervision, delegation strategies.</li>
<li>RAG, GraphRAG and knowledge graph design and implementation.</li>
<li>Vector databases and similarity search systems.</li>
<li>Graph databases (ArangoDB, Neo4j, Neptune) and property graph modelling.</li>
<li>Data engineering: ETL pipelines, document processing, schema design for AI applications.</li>
<li>Cloud platforms (GCP preferred, AWS/Azure also relevant) and containerisation (Docker).</li>
<li>Observability and monitoring for LLM applications (tracing, metrics, cost tracking).</li>
<li>Secure coding practices for regulated industries and sensitive data handling.</li>
<li>Frontend experience (React/Next.js) for rapid prototyping of client demos.</li>
</ul>
<div>&nbsp;</div>
<div><strong>What We Offer</strong></div>
<div>&nbsp;</div>
<div>Work on impactful, cutting-edge products powered by artificial intelligence and machine learning.&nbsp;</div>
<div>Be part of an agile, close-knit team that values creativity, quality, and continuous learning.</div>
<div>&nbsp;</div>
<div>A flexible working environment, with typically 2 days of hybrid working in our Belfast office, and one of the best work-life balances you’ll find:&nbsp;</div>
<ul>
<li>A (Mon to Thurs) 4-day work week during the holidays - July, August and December</li>
<li>The last Friday of every month off</li>
<li>Early finish every working Friday at 3pm</li>
<li>25 days of annual leave, plus all NI bank holidays</li>
<li>EMI Share options in a rapidly growing scale-up&nbsp;</li>
</ul>
<div>&nbsp;</div>
<div>Closing date: Open until filled</div>
</div></body></html>

<div>
<div><strong>Department: Engineering</strong></div>
<div><strong>Hours: Full-time</strong></div>
<div><strong>Reporting to: Head of Solutions Engineering</strong></div>
<div><strong>Salary: £70,000 - £85,000 p.a. (+EMI share options)</strong></div>
<div> </div>
<h2>
<br><strong>About Whitespace</strong>
</h2>
<p>Whitespace leads in creating smarter, safer AI solutions for enterprises. As AI presents transformative opportunities, many companies struggle to harness its full potential.</p>
<div>Whitespace bridges this gap with Collective - The AI Operating System for high-assurance environments. Built for scale, trust and action - even in the most secure, complex or disconnected settings.</div>
<div> </div>
<div>We're not just building AI systems. We're laying the foundation for a future where humans and machines work together like never before.</div>
<h2>
<br><strong>Role Summary</strong>
</h2>
<div>The successful AI Solutions Engineer will extend and enhance our AI Operating System, which leverages LLMs to solve industry-specific challenges across defence, legal, health, infrastructure and management consulting sectors.</div>
<div> </div>
<div>This is a hands-on lead role focused on rapidly prototyping and deploying AI-powered solutions. Working directly with clients, you will translate their needs into scalable, production-ready AI applications using modern frameworks and techniques.</div>
<h2>
<br><strong>Duties &amp; Responsibilities</strong>
</h2>
<h2><strong>Technical Development</strong></h2>
<ul>
<li>Develop platform functionality using Python, building APIs and integrations to extend capabilities for diverse client needs.</li>
<li>Design and implement LLM-powered applications and workflows using open source models such as Llama, Qwen and Gemma, as well as those online models from OpenAI, Gemini, etc.</li>
<li>Build AI agents with tool/function calling, prompt engineering and appropriate guardrails using frameworks such as OpenAI AgentSDK, LangGraph or LlamaIndex.</li>
<li>Implement testing and evaluation frameworks for LLM applications, covering prompt testing, output quality metrics and agent behaviour validation.</li>
<li>Apply relevant AI technologies as needed, including retrieval systems (RAG, GraphRAG), knowledge graphs, vector databases or data pipelines.</li>
</ul>
<div> </div>
<h3><strong>Solution Design and Implementation</strong></h3>
<ul>
<li>Design and deliver scalable, efficient solutions tailored to client-specific requirements whilst balancing innovation with practical constraints around compliance, performance, cost and security.</li>
<li>Lead technical discussions, diagnose complex challenges and provide guidance to less experienced team members.</li>
</ul>
<div> </div>
<h3><strong>Client Engagement and Collaboration</strong></h3>
<ul>
<li>Work directly with clients to gather requirements and translate them into actionable AI-powered solutions, moving rapidly from concept to working prototype.</li>
<li>Communicate complex technical concepts effectively to technical and non-technical stakeholders, including system capabilities and limitations.</li>
<li>Mentor junior engineers and contribute to technical knowledge sharing within the team.</li>
</ul>
<div> </div>
<h2><strong>Role Requirements</strong></h2>
<h3><strong>Work Experience</strong></h3>
<ul>
<li>At least five years as a software engineer on commercial platforms, with demonstrable experience building production LLM-powered applications.</li>
<li>Proven experience with API-level LLM usage, including tool/function calling, prompt engineering and evaluation.</li>
<li>Experience with agent frameworks (OpenAI AgentSDK, LangGraph, LlamaIndex Agents or similar).</li>
<li>Experience developing APIs using FastAPI or similar frameworks and integrating with third-party platforms.</li>
<li>Direct client-facing experience gathering requirements and delivering technical implementations.</li>
<li>Experience within agile development workflows and engineering teams.</li>
</ul>
<div> </div>
<h3><strong>Skills &amp; Abilities</strong></h3>
<ul>
<li>Strong Python (or similar) programming skills with a focus on production-grade applications.</li>
<li>Excellent communication abilities, translating complex technical concepts for diverse audiences.</li>
<li>Strong analytical and problem-solving approach, identifying scalable and reusable solutions.</li>
<li>Leadership qualities, including technical mentorship, team collaboration and line management.</li>
<li>Ability to align solutions with business goals and industry-specific constraints.</li>
<li>Self-sufficient contributor capable of working independently and seeking support when needed.</li>
</ul>
<div> </div>
<div><strong>Nice to Have</strong></div>
<div> </div>
<div>
<br>The following are examples of specialised areas that would be valuable. Deep expertise in some of these areas is preferred over surface-level knowledge across all domains.</div>
<div> </div>
<ul>
<li>Open source LLMs (Llama, Qwen, Gemma, GPT OSS) and local deployment strategies.</li>
<li>Frameworks and protocols such as Model Context Protocol (MCP) or Agent-to-Agent (A2A).</li>
<li>LLM evaluation tooling (OpenAI Evals, LangSmith, custom evaluation harnesses).</li>
<li>Advanced agent patterns: multi-agent systems, supervision, delegation strategies.</li>
<li>RAG, GraphRAG and knowledge graph design and implementation.</li>
<li>Vector databases and similarity search systems.</li>
<li>Graph databases (ArangoDB, Neo4j, Neptune) and property graph modelling.</li>
<li>Data engineering: ETL pipelines, document processing, schema design for AI applications.</li>
<li>Cloud platforms (GCP preferred, AWS/Azure also relevant) and containerisation (Docker).</li>
<li>Observability and monitoring for LLM applications (tracing, metrics, cost tracking).</li>
<li>Secure coding practices for regulated industries and sensitive data handling.</li>
<li>Frontend experience (React/Next.js) for rapid prototyping of client demos.</li>
</ul>
<div> </div>
<div><strong>What We Offer</strong></div>
<div> </div>
<div>Work on impactful, cutting-edge products powered by artificial intelligence and machine learning. </div>
<div>Be part of an agile, close-knit team that values creativity, quality, and continuous learning.</div>
<div> </div>
<div>A flexible working environment, with typically 2 days of hybrid working in our Belfast office, and one of the best work-life balances you’ll find: </div>
<ul>
<li>A (Mon to Thurs) 4-day work week during the holidays - July, August and December</li>
<li>The last Friday of every month off</li>
<li>Early finish every working Friday at 3pm</li>
<li>25 days of annual leave, plus all NI bank holidays</li>
<li>EMI Share options in a rapidly growing scale-up </li>
</ul>
<div> </div>
<div>Closing date: Open until filled</div>
</div>