At a Glance
- Tasks: Build AI agents that streamline revenue team tasks and tackle messy GTM data.
- Company: Join a pioneering tech company focused on innovative AI solutions.
- Benefits: Enjoy 25 days holiday, competitive salary, and remote work flexibility.
- Other info: Opportunity to hire and shape a team culture around data quality.
- Why this job: Be the first engineer shaping AI technology and making a real impact.
- Qualifications: 5+ years in backend development with a focus on data-heavy systems.
The predicted salary is between 70000 - 90000 £ per year.
We're building AI agents for GTM — agents that do the work of a revenue team end-to-end: researching accounts, drafting outreach, updating the CRM, triaging inbound, prepping calls, following up. GTM data is the messiest data in the enterprise. It lives across 10+ systems, it's stale, it's permissioned, and full of half-truths people typed into Salesforce on a Friday afternoon. Building agents on top of this without hallucinating and actually getting the job done at scale is the real engineering problem.
You'd be the first engineer. The hard part isn't the agent loop — it's the data and context layer underneath: pulling from Salesforce, HubSpot, Gong, Slack, Notion, Drive and a long tail of broken APIs, then turning that mess into the precise, fresh, permission-aware context an agent needs to take a real action. Most of your hardest engineering time will be on the data side: ingestion, modelling, freshness, retrieval quality, evals, latency, permissions.
Own the data and context pipeline end-to-end: connectors, ingestion, schema modelling, chunking, embedding, indexing, hybrid search, reranking, serving. Own the agent runtime on top: tool use, planning, multi-step execution, error recovery. Build the eval harness before shipping anything new. We don't ship on vibes. By month six you'll have hired the second engineer and shaped the team's culture around data quality, evals, latency, and product taste.
- 5+ years of production backend experience, with meaningful time on data-heavy systems — retrieval, search, recsys, streaming pipelines, or ML infra with real users and real SLAs.
- You think data first. Bad data in, bad agents out, and you've felt that pain.
- Shipped a non-trivial RAG, semantic search, or agent system end to end. Strong opinions on hybrid retrieval. You know when BM25 beats embeddings, when SQL beats both, and you've made those calls in production.
- (Nice to have) Python or Go fluency.
- Multi-tenant systems with row- or document-level access control. Messy GTM stack integrations — Salesforce, HubSpot, Gong, Outreach, Apollo — and the scars to show for it.
- Data governance or security overlap: lineage, audit trails, PII handling, prompt injection defence.
Founders call (60 min, remote). Walk us through a data-heavy system you've built.
25 days holiday + UK
Tech / AI Specialist Tech / AI Specialist in London employer: Stealth AI Company
As a Tech / AI Specialist at our innovative company, you'll be at the forefront of building cutting-edge AI agents that transform messy GTM data into actionable insights. We pride ourselves on fostering a collaborative work culture that values data quality and employee growth, offering 25 days of holiday and opportunities to shape the team's future while working in a dynamic environment. Join us in a location that encourages creativity and technical excellence, making it an exceptional place for meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Tech / AI Specialist Tech / AI Specialist in London
✨Tip Number 1
Get your networking game on! Reach out to folks in the industry, especially those who work with data-heavy systems. A casual chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing projects related to data ingestion, retrieval, or any AI agents you've built. This gives us a taste of what you can do and how you think about data.
✨Tip Number 3
Prepare for the interview by diving deep into our tech stack. Familiarise yourself with Salesforce, HubSpot, and other tools mentioned in the job description. We love candidates who come in with knowledge and ideas on how to tackle our challenges.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows us you’re genuinely interested in joining our team.
We think you need these skills to ace Tech / AI Specialist Tech / AI Specialist in London
Some tips for your application 🫡
Show Your Data Passion:When you're writing your application, make sure to highlight your love for data. We want to see how you've tackled messy data in the past and how you think about data quality. Share specific examples that showcase your experience with data-heavy systems!
Be Clear and Concise:We appreciate clarity! Keep your application straightforward and to the point. Avoid jargon unless it’s necessary, and make sure your skills and experiences shine through without any fluff. Remember, we’re looking for someone who can communicate effectively.
Tailor Your Application:Don’t just send a generic application. Take the time to tailor your responses to our job description. Mention specific technologies or methodologies we've highlighted, like hybrid retrieval or data governance, and explain how your background aligns with our needs.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Stealth AI Company
✨Know Your Data Inside Out
Since the role revolves around messy GTM data, make sure you can discuss your experience with data-heavy systems in detail. Be ready to explain how you've handled data ingestion, modelling, and retrieval quality in past projects.
✨Showcase Your Engineering Mindset
Prepare to walk through a non-trivial system you've built from end to end. Highlight your decision-making process regarding hybrid retrieval methods and how you've tackled challenges like bad data affecting agent performance.
✨Familiarise Yourself with the Tech Stack
Brush up on the tools mentioned in the job description, like Salesforce, HubSpot, and Gong. Being able to discuss your experience with these platforms will show that you're not just a tech whiz but also understand the business context.
✨Cultural Fit is Key
As you'll be shaping the team's culture, think about how you can contribute to a focus on data quality and product taste. Prepare examples of how you've fostered a positive engineering culture in previous roles.
