AI Engineer - Talent pool

AI Engineer

Location: London, Hybrid (minimum 2 -3 days per week in office)

Type: Full-Time, Permanent

Reports to: Due to the nature of our work, candidates must be eligible for Security Clearance.

We have a number of contract and permanent positions in the pipeline and we are therefore keen to see what exceptional AI Engineers are available in the market and excited to join our AI mission.

Join Our Mission

At QuantSpark, we're transforming how data and AI serve society. Our team partners with forward-thinking organisations across multiple sectors to harness the power of analytics and artificial intelligence-creating meaningful impact that extends far beyond financial outcomes.

Our impressive client portfolio:

• Private Equity & Financial Services: We work with top-tier investment firms, global financial institutions, and leading wealth management companies, providing portfolio performance analytics, AI-powered value creation, and risk identification tools.
• Retail & Consumer: Our solutions help major national retailers, high-street brands, and premium consumer goods companies optimise inventory, enhance price competitiveness, and deliver personalised customer experiences.
• Asset Management: We build AI-powered investment decision support systems, alternative data integration platforms, and automated risk management solutions for prestigious asset management firms.
• Public Sector: We're trusted by multiple UK government departments and public sector organisations to deliver predictive maintenance systems, supply chain optimisation, and process automation.
• SaaS, Manufacturing & More: From innovative SaaS providers to global manufacturing leaders, our cross-industry expertise ensures we bring diverse perspectives to complex challenges.

Role Requirements

Drive Innovation and Transformative Solutions with Data & AI

You started in data science or ML - you understand models, you've worked with data at scale, and you know how to evaluate whether something actually works. But over the last couple of years, you've made a deliberate move toward building: shipping LLM-powered applications, designing pipelines that run in production, and taking ownership of systems rather than just experiments.

That's exactly the journey we're looking for.

At QuantSpark, you'll apply that foundation to real client problems - designing and delivering AI systems across financial services, the public sector, and beyond. Our platform and infrastructure teams handle the deeper deployment layer, so you can focus on what you do best: turning complex problems into reliable, production-grade AI.

You Should Hit the Apply Button If

You've crossed the line from experimentation to production. You've moved beyond notebooks and prototypes. You have hands on experience shipping LLM powered applications into real environments - and you've lived with the consequences: edge cases, latency, prompt drift, and keeping things working when the context gets messy.

You bring ML rigour to AI engineering. Your data science or ML background is an asset here. You know how to design evaluations (evals), think carefully about model quality, and instrument systems for monitoring and drift detection. You don't just ship - you measure.

You design retrieval and context pipelines with intention. You've built RAG systems and understand the trade offs: chunking strategies, retrieval quality, context window management, and where these pipelines break under real world conditions.

You've worked with agentic systems. You have experience building or contributing to multi agent workflows - tool use, orchestration, memory management - and you understand the failure modes that come with giving models autonomy.

Your code is production quality. Coming from a data background, you've made the deliberate effort to close the software engineering gap. You write clean, testable, version controlled code, work confidently with APIs and cloud environments, and collaborate effectively with software engineers without needing translation.

You communicate with clarity. You can explain trade offs to non technical stakeholders, write documentation others actually use, and push back constructively when requirements don't make sense.

Nice to Have

• Experience working in regulated industries such as financial services or the public sector.
• Familiarity with MLOps concepts - model lifecycle management, monitoring pipelines - even if this isn't your primary focus.
• Exposure to classical ML in production - forecasting, classification, optimisation - alongside newer LLM based approaches.

I Want to Work for a Company That

• Values the full journey - from data science roots to production AI engineering - and sees both as strengths.
• Ships production grade AI and holds engineering quality to a high standard.
• Takes responsible AI seriously - including fairness, transparency, and the societal impact of what we build.
• Gives engineers real ownership and room to shape the work, not just execute it.

I'm Looking to Work With

Talented data scientists, software engineers, product managers, and client stakeholders who care about outcomes, not just outputs - and teams where clear communication and rigorous thinking are the norm.

In 3-5 Years I Want to Be

A recognised expert in building and evolving LLM powered systems that drive real world impact.

• Shaping AI architecture decisions and contributing to how the discipline matures at QuantSpark.
• Mentoring others - particularly those earlier in the data to engineering transition - and helping raise the bar for AI engineering practice across the team.

Perks & Benefits

• £6,000 annual training & conference budget to support your technical and career development
• Up to 6% matched pension for your long term security
• Comprehensive private healthcare through Vitality
• Work from anywhere in the world for up to 20 days per year
• 25 days holiday + bank holidays + flexibility to buy/sell up to 5 additional days
• Sustainable commuting support through our cycle to work scheme
• Engaging Central London office environment with quality refreshments, regular team socials, and a vibrant atmosphere
• Exclusive discounts on retail, travel, technology, and fitness memberships
• Regular tech talks, knowledge sharing sessions, and innovation time
• Dog friendly office
• Tech mentorship programme

Equal Opportunities

We are committed to building a diverse and inclusive team. Different perspectives, identities, and experiences make us stronger-both as people and as a business. All qualified applicants will be considered without regard to sex, sexual orientation, marital status, race, nationality, religion, disability, or age. We currently have an underrepresentation from women, BAME, disabilities and LGBTQ communities. As such, we particularly welcome applicants from these groups.