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AI/Agent Engineer

Vega
LondonOn-site15h ago
Employment
Full-time

About the role

Location: London

Office attendance: 4 days per week in-office (Paddington)

About Vega

Vega is an early-stage startup. There's no playbook, limited structure, and the expectations are high. Our goal is to build a generational company – we know this is not for everyone, but our commitment is that, for those who it is, this will be a career-defining place to be.

Vega is unlocking scale for alternative asset managers. Private markets are shaping into one of the most influential forces in the global economy over the coming decades, with more than $20 trillion in AuM today and expected to already triple by 2032. Today, the industry is at an inflection point as it enters an era of hyper-growth, increased complexity, and brand-new demands. To competitively service and scale their client base across the entire investment lifecycle, managers need a technological transformation. Vega is delivering the industry’s purpose-built infrastructure with AltOS – a first-of-its-kind AI-powered operating system where all client work gets done.

Vega’s founding team consists of alternatives specialists from KKR, Blackstone, Elliott, and Goldman Sachs, along with top product and engineering talent from successful fintech scale-ups like Revolut and Trade Republic. Vega has raised over $28M in funding from Apollo, Motive Ventures, Picus Capital, and 60 senior executives from the alternative investment industry, with over $300B assets under administration on our platform.

To learn more, visit:

Who We're Looking For

Not a CV. A track record of building things.

We want someone who has spent the last few years obsessing over what AI can actually do. Someone with projects, products, repos, or experiments to show for it.

We care far more about what you've built than where you've worked or studied.

Maybe you've built an LLM-powered tool people actually use. Maybe you've designed an agent workflow that solves a real problem. Maybe you've fine-tuned models, built side projects, won hackathons, or contributed to open source.

What matters is that you ship, think from first principles, and get restless when you're not building.

What You'll Do

  • Build AI-powered features across AltOS, including agents, document intelligence, workflow automation, and knowledge retrieval systems

  • Work directly with founders and engineering teams to take ideas from concept to production

  • Own problems end-to-end, from scoping and architecture through to shipping and iteration

  • Help define how AI is applied across Vega's products and internal workflows

  • Stay close to developments in AI and bring what matters into production

Technologies

  • AI & LLM: AWS Bedrock, Antrophic SDK, RAG with Bedrock Knowledge Bases, Multi-agent orchestration,

  • Back-end: Java 21, Spring Boot, REST, Postgres/Jooq/Flyway, JUnit/TestContainers/Mockito, AWS (EC2, RDS, Cognito, S3, KMS), Containerization (Docker / kubernetes)

  • Front-end: TypeScript, React, and Tailwind CSS

  • Cloud & Infra: AWS (Bedrock, S3, KMS, SQS, CloudFront, Cognito, RDS), Kubernetes, Helm, GitHub Actions, Docker

Interview Process

  • Stage 1 - Founder screening: An introductory conversation covering your background, motivations, and interest in Vega.

  • Stage 2 - Technical conversation: A discussion with one of our AI senior engineers focused on your experience, projects, technical decision-making, and approach to building AI systems.

  • Stage 3 - In-person problem solving session: A collaborative session in our London office where you'll explore a day-day problem, discuss solutions, write some code together with our engineers, and talk through your approach.

Why Join Vega?

  • Help define the future of AI at a well-funded company operating in a large and rapidly growing market

  • Work directly with founders and senior leadership

  • High autonomy, trust, and responsibility from day-one

  • Build production AI systems used by leading alternative asset managers

  • Competitive salary and equity package

  • Benefits: private medical insurance, gym membership, learning budget and many more

Perks & benefits

  • Medical Insurance
  • Learning Budget
  • Free Gym Membership
  • Equity Compensation

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