Artificial Intelligence Engineer, QuantSpark
+ EMI Share Options + Up to 10% personal performance bonus
2 days a week in office (Blackfriars, London)
QuantSpark is revolutionising how data and AI serve society
Open for applications
QuantSpark is revolutionising how data and AI serve society
21-100 employees
Open for applications
+ EMI Share Options + Up to 10% personal performance bonus
2 days a week in office (Blackfriars, London)
21-100 employees
Company mission
Strategy consultancy meets product studio: We build AI-powered tools that turn data into decisive competitive advantage.
Role
Who you are
- Seniority: Mid to Senior (SFIA 4)
- SC Eligibility Required: You do not need to already hold Security Clearance, but you must be eligible to undergo the vetting process
- You've crossed the line from experimentation to production. You've shipped LLM-powered applications and lived with the consequences — edge cases, latency, prompt drift, keeping things working when context gets messy
- You bring ML rigour to AI engineering. Evaluations, model quality, monitoring, drift detection. You don't just ship — you measure
- You've designed RAG and agentic systems with intention. You understand chunking, retrieval quality, context management, and where these systems break under real conditions
- You're comfortable across the modern AI toolchain. Claude Code, Codex, Power Automate, n8n. Pragmatic about choosing the right tool
- Your code is production-quality. Clean, testable, version-controlled. You collaborate effectively with software engineers without needing translation
- You treat client problems as your own. Commercially aware, comfortable with the “why,” and you'd rather over-own a difficult delivery than hide behind process
- You communicate clearly. You can explain trade-offs to non-technical stakeholders and push back constructively when requirements don't make sense
- Nice to have: experience in regulated environments (financial services, public sector); MLOps practice; pre-sales or technical proposal experience; familiarity with responsible AI practice
What the job involves
- We’re looking for an AI Engineer who has already moved from experimentation into production and wants to go further
- You may have started in data science or Machine Learning, but now you’re happiest building reliable systems: shipping LLM-powered applications, designing evaluation frameworks, creating retrieval pipelines, and making sure things keep working when real users, messy data, and changing requirements get involved
- At QuantSpark, you'll apply that foundation to real client problems
- Some engagements call for a carefully orchestrated AI pipeline; others need a well-chosen low-code tool wired up properly
- The skill is knowing which approach fits the problem, making it work reliably, and creating measurable impact for the client
- Lead delivery on client engagements. You'll own the technical shape of AI and ML workstreams from scoping through handover — making the build-versus-buy-versus-wire-together call, and being the engineer the client trusts in the room
- Help us win the next engagement. You'll work alongside our Consulting team on live opportunities — translating client problems into credible technical approaches, running discovery sessions, and shaping proposals that are honest about what AI can and can't do
- Build automation that lands. From orchestrated AI pipelines to a well-wired Power Automate flow, you'll deliver the solution that actually solves the client's problem
- Turning a PE-backed business's unstructured operational data — contracts, claims, supplier correspondence — into a usable signal, and building the systems that keep doing it
- Working with a public sector team on fraud detection or predictive maintenance, with the rigour and traceability those clients need
- Designing an agentic workflow that compresses a week of manual analyst work into hours, with guardrails the client can trust
- Replacing a brittle Power Automate flow with something better — or building the right one because that's actually what the problem needs
- You'll work across the modern AI toolchain — the choice of tool is part of the engineering judgment:
- Production LLM applications — RAG, retrieval pipelines, prompt-engineered workflows, with the evaluation work that makes them reliable
- Multi-agent systems — tool use, orchestration, memory, and guardrails that keep autonomy useful
- Classical ML in production — forecasting, classification, optimisation, because not every problem needs a transformer
- Low-code and workflow automation — Power Automate, n8n, used deliberately when they're the right tool
- AI harness tooling — Claude Code, Codex, and the broader AI development toolchain
- Most consultancies make engineers pick a lane, we feel our hybrid approach is a better match for the problems clients bring us
- You'll sit within our Engineering team and work day-to-day with Product & Consulting and client stakeholders. We’re a genuinely curious, low-ego bunch who care about doing meaningful work. We keep that culture deliberate — internal guilds, lunch-and-learns, regular talks and events in the office, and hackathons where you'll build a career alongside peers from across the business
Salary benchmarks
Our take
QuantSpark helps governments and businesses to strategically apply data science through the development of complex decision-making software. Primarily, its work involves analysing large datasets and systems in order to understand customer behaviour and help clients make informed decisions for strategic planning in sales and marketing.
In recent years, big data has become central to the operation of businesses large and small, and this has led to great demand for data scientists fluent in sophisticated modelling and analysis. QuantSpark seeks to go a step further, providing a service which combines data science with commercial insight- effectively providing both services through one transaction. By doing this, QuantSpark hopes to offer clients a more meaningful insight into their data than a standard consultancy could.
Already, the company has an impressive client list, including the UK Government, the Australian Government and Bain Capital. QuantSpark's tools and solutions are developed to become embedded in its clients' operations, ensuring a long-lasting relationship between them, and meaning that, as QuantSpark continues to expand its client base, its model should allow it to see continued success in the future.
Steph
Company Specialist at Welcome to the Jungle
Company
Company benefits
- Tech for good: We are passionate about giving our team the chance to have a real social impact and will have the opportunity to work on a wide variety of impactful projects
- Training budget: Everyone in QuantSpark has £6,000 training budget and 12 ring-fenced days a year to spend on their own professional development
- Work abroad for up to 1 month per year
- Generous EMI Share Options scheme
- Socials, clubs and guilds to connect with colleagues and share knowledge
- Hybrid working (2-3 days in office per week)
- Dog friendly office
- Cycle to work scheme. Onsite showers
- 25 days annual leave + bank holidays + buy/sell 5 days annual leave
- Pension matched up to 6%
- Vitality Private healthcare
- Annual performance bonus: Company profit share scheme and a personal performance bonus of 10%
Company values
- Problem Solving Power: We thrive on solving the biggest challenges with data, strategy, and AI - delivering clarity from complexity.
- Innovation That Lasts: We go beyond solutions - reimagining operations and scaling impactful innovation across industries.
- Results That Matter: We focus on outcomes that count - driving efficiency, profitability and positive societal impact.
Company HQ
London, UK
Articles
Leadership
Adam Hadley
(Co-Founder & CEO)Entrepreneur and CBE Adam leads QuantSpark and Tech Against Terrorism, using AI and analytics to tackle global challenges, strengthen security, and foster economic growth in the UK.
Diversity, Equity & Inclusion at QuantSpark
- As an AI-first consultancy tackling complex challenges from economic crime to government fraud prevention, we know that diverse perspectives drive better solutions. Different backgrounds, experiences and ways of thinking aren't just nice to have—they're essential to building technology that works for everyone and solving problems others miss.
- Transparent progression frameworks ensuring fair opportunities for growth regardless of background
- Inclusive recruitment practices designed to attract talent from underrepresented groups in tech and data science
- Regular culture initiatives like our peer feedback sessions, workshops and AMA's where we actively shape our workplace together
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