AI Applied Engineer

We are an office-first company and expect regular in-person collaboration as part of this role. You should also be comfortable collaborating across time zones (US, UK, India).

We offer a competitive package designed to support you both inside and outside of work:

• Base Salary: Factors that may impact the agreed upon salary within the range for a particular candidate include years of experience, level of education obtained, skill set, and other external factors.
• Performance Bonus: bonus target
• Equity: Meaningful stock options so you share in our growth
• Time Off: Flexible PTO
• Health & Wellbeing: Private Medical Insurance (UK) 
• Retirement: Pension

Auquan develops autonomous AI agents that eliminate the repetitive, manual work slowing down financial institutions. Our technology supports credit, investment, ESG, and compliance workflows for leading firms including Goldman Sachs, UBS, CVC, and MetLife. Today, 40% of the world’s top 50 financial institutions use Auquan to remove manual processes, speed up decision-making, and achieve greater strategic impact.

With teams growing across the US, UK, and India, we’re building an elite force of innovators ready to redefine what’s possible with AI and machine learning.

About the role
This role sits at the intersection of systems architecture, agentic AI workflows, and customer-facing problem solving. You’ll design multi-agent systems, build reusable primitives, and convert complex financial workflows into scalable automated products.
You’ll work directly with leading investment firms and own the lifecycle of every agent you build—from design to reliability, deployment, and scale.
Team & Culture
High-agency, high-velocity, no-politics.
We move fast, unblock ourselves, work directly with customers, give clear feedback, and minimise process. We’re building the platform that automates analytical work across finance — a category-defining opportunity.
If you want to own meaningful outcomes, build high-leverage AI systems, and move faster than almost anywhere else, you’ll fit right in.

• Take ambiguous workflow requests and turn them into scoped, architected, implemented, and deployed multi-agent systems
• Build reliable multi-step, multi-agent workflows used in production by financial institutions
• Own reliability, latency, success metrics, and customer adoption
• Work directly with customer engineering teams to deliver smooth deployments
• Convert bespoke workflows into reusable platform primitives and components
• Build orchestration logic, tools, templates, and pipelines used across engineering pods
• Ship V1s in days, operate with high agency, tight prioritisation, and strong defaults
• Identify patterns across customers and turn them into reusable systems
• Influence architecture and direction of core platform components
• Use AI for coding, testing, debugging, workflow design, and documentation
• Build evals, safety nets, and AI-native engineering workflows

Must-Haves

• 4+ years of software development in fast-paced, product-focused environments
• Owned a subsystem or workflow end-to-end (requirements → architecture → implementation → launch)
• Strong Python fundamentals; think in primitives, patterns, and systems
• Already use AI to automate work or build LLM-powered workflows
• Comfortable translating customer ambiguity into crisp technical solutions
• Able to unblock yourself through learning, experimentation, and AI tools
• Thrive under tight deadlines, high expectations, and minimal process
• You'll have a solid grasp of our tech stack: Python, React / NextJS, Fast API, MongoDB, Redis

Nice-to-Haves

• Built or orchestrated multi-step LLM or agentic workflows
• Experience with financial workflows (credit, investment, ESG, risk)
• Infra/ops exposure (Kubernetes, Terraform, Azure/AWS, CI/CD, observability)
• Experience at early-stage startups
• Built internal frameworks, tooling, or templates used by multiple teams
• Experience with evals, guardrails, or workflow orchestration systems