At a Glance
- Tasks: Build AI agents that streamline revenue team tasks and manage 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 60000 - 80000 £ 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 bank holidays.
Tech / AI Specialist Tech / AI Specialist employer: Stealth AI Company
Join a pioneering team as a Tech / AI Specialist, where you'll be at the forefront of building innovative AI agents that transform messy GTM data into actionable insights. Our collaborative work culture prioritises data quality and employee growth, offering 25 days of holiday plus UK bank holidays, and the opportunity to shape a new engineering team from the ground up. With a focus on meaningful projects and a supportive environment, this role is perfect for those looking to make a significant impact in the tech landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Tech / AI Specialist Tech / AI Specialist
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to data-heavy systems. We want to see what you can do, so make it easy for us to find your best work!
✨Tip Number 3
Prepare for the interview by diving deep into our tech stack. Familiarise yourself with the tools we use, like Salesforce and HubSpot, and be ready to discuss how you've tackled similar challenges in the past. We love candidates who come prepared!
✨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 at StudySmarter.
We think you need these skills to ace Tech / AI Specialist Tech / AI Specialist
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 of projects where you’ve had to deal with complex data systems.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to understand your experience and skills without wading through fluff.
Tailor Your Application:Make sure to customise your application for the Tech / AI Specialist role. Reference the job description and align your skills and experiences with what we’re looking for. Show us that you get what we do and how you can contribute!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Stealth AI Company
✨Know Your Data Inside Out
Since the role revolves around handling messy GTM data, make sure you can discuss your experience with data-heavy systems. Be ready to explain how you've tackled issues like data ingestion, modelling, and retrieval quality in previous projects.
✨Showcase Your Engineering Mindset
Prepare to walk through a specific project where you built a non-trivial RAG or semantic search system. Highlight your decision-making process regarding hybrid retrieval methods and how you ensured data quality throughout the project.
✨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 and how you've integrated them in past roles will show you're a great fit for the team.
✨Cultural Fit Matters
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 positions, especially around collaboration and continuous improvement.
