
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Location: London
Career Level: 9 Consultant
About QuantAI
QuantAI is building cutting-edge AI-native decision-system assets for energy, commodities, financial, trading, and industrial operations. We are looking for engineers who can take strong quantitative and artificial intelligence (AI) work and turn it into enterprise-safe products: interfaces, packaged desktop applications, APIs, services, workflow systems, and demos that are credible enough for pilots and durable enough for scaled delivery.
Success here
Success here is not raw model novelty or polished demos in isolation. It is strong algorithms wrapped in workflow, governance, evaluation, and packaging. This role is engineer-first and shipping-first. The engineering covers two surfaces that both ship as product: conventional systems on one side, agent-assisted systems on the other. The team is too small for either to be someone else's problem, and you should be able to operate across both -- though you will likely lead with strength in one.
What you'd work on
- Turn quantitative prototypes into reusable tools, services, packaged desktop applications, interfaces, and workflow products that can move from internal demo to client pilot to scaled offer.
- Ship across both cloud-hosted services and locally distributed desktop applications, including Electron-based apps when the workflow or client environment calls for it.
- Build enterprise hardening into the productization layer, including authentication, role-based access control (RBAC), observability, security, release quality, cost controls, and deployment discipline.
- Build evaluation, regression, and release discipline into the productization layer so model logic and agent behavior remain measurable as systems change.
- Work closely with the quant lead so model logic, evaluation intent, and governance requirements survive the move into production.
- Make pragmatic architecture choices across large language models (LLMs), deterministic rules, and hybrid systems based on value, latency, cost, and reliability.
- Help shape repeatable build patterns so strong prototypes become faster, more reliable, and more reusable over time.
Platforms and interfaces
- Own data flows, APIs, services, model-serving surfaces, front-end and desktop application surfaces, continuous integration and continuous delivery (CI/CD), and demo hardening.
- Build the systems that make quantitative work feel polished, reliable, and enterprise-ready for expert users and client stakeholders.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Agent-assisted systems
- Own the agentic harness layer — evaluation frameworks, reviewer loops, control-plane behavior, orchestration, and tool integration — that applications and MCPs wrap around.
- Design opinionated harnesses that expose through MCP or similar integration patterns without overfitting to one vendor or one moment in the tooling market.
What good looks like
Must-have
- Bachelor's degree in computer science, engineering, mathematics, physics, economics, or a related field. An associate degree is acceptable with at least 2 additional years of directly relevant experience and clear evidence of shipped engineering work.
- Minimum 3 years of experience in consulting or other client-facing technical delivery roles, with evidence that you have helped move products, internal tools, or workflow systems beyond proof-of-concept stage.
- Minimum 3 years of hands-on experience in one or more of the following areas: backend services, APIs and integrations, full-stack delivery, data pipelines, model-serving or machine learning workflows, or agentic orchestration systems.
- Strong coding ability in Python plus one complementary engineering surface such as TypeScript or JavaScript, front-end delivery, cloud or platform engineering, or infrastructure automation.
- Sound engineering judgment around enterprise hardening and evaluation, including experience with several of the following: authentication, role-based access control (RBAC), observability, security, release discipline, regression testing, or experiment frameworks for AI, machine learning, or agentic workflows
Nice-to-have
- Experience with tool-using systems, retrieval, evaluation pipelines, agent orchestration, or MCP-style integrations.
- Experience building expert-facing interfaces, workflow products, or technical demos that had to stand up in front of real users.
- Experience packaging desktop applications or supporting Windows-heavy enterprise environments.
- Exposure to forecasting, anomaly detection, optimization, time-series systems, or other decision-support workflows.
- Experience in energy, commodities, financial, trading, market operations, or industrial workflows.


Get help with your application
Your very own career expert that helps elevate your application to the next level.
Team and environment
QuantAI sits between quantitative research, agentic engineering, and product delivery inside Accenture. The team is small, hands-on, and built for people who want visible ownership and the chance to build something lasting.
The goal is not one-off demos or deckware. The goal is reusable assets clients can trust, buy, and scale.
Different strengths can thrive here, but on a team this size everyone works across both engineering surfaces. We care more about demonstrated depth in one area plus real fluency in the other than about a shallow checklist match across everything.
You should expect direct technical feedback, growing scope, and close collaboration with quants and practice leadership.
This is a small-team build environment with real route-to-market access in energy, commodities, financial, trading, and industrial decision systems. The work needs to stand up in front of business decision makers and operators, not just engineers.
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
Visit us at www.accenture.com
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location