At a Glance
- Tasks: Build AI agents that streamline revenue team tasks and manage messy GTM data.
- Company: Join a pioneering tech startup focused on innovative AI solutions.
- Benefits: Enjoy 25 days holiday, competitive salary, and flexible remote work options.
- Other info: Opportunity to lead a team and influence company culture from day one.
- Why this job: Be the first engineer shaping the future of AI in revenue operations.
- 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 bank holidays.
D T Technician employer: Stealth AI Company
Join a pioneering team at the forefront of AI development, where you'll have the opportunity to shape the future of revenue operations. With a strong emphasis on data quality and engineering excellence, we foster a collaborative work culture that prioritises employee growth and innovation. Enjoy generous benefits including 25 days of holiday plus UK bank holidays, and be part of a dynamic environment that values your contributions and encourages you to take ownership of your projects.
StudySmarter Expert Advice🤫
We think this is how you could land D T Technician
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. 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
Prepare for those interviews by brushing up on your data-heavy systems knowledge. We want to see how you think about data quality and retrieval, so be ready to share your experiences and opinions!
✨Tip Number 3
Don’t forget to showcase your projects! If you've built something cool related to data ingestion or hybrid retrieval, make sure to highlight it. We love seeing real-world applications of your skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates who are ready to tackle messy GTM data with us.
We think you need these skills to ace D T Technician
Some tips for your application 🫡
Show Your Data Passion:When you're writing your application, let us see your love for data! Talk about your experiences with data-heavy systems and how you've tackled messy data challenges. We want to know how you think 'data first' and how you've made impactful decisions in your past roles.
Be Specific About Your Experience:Don't just list your skills; give us the juicy details! Share specific projects where you've worked on retrieval, search, or any agent systems. The more we can see your hands-on experience, the better. Remember, we’re looking for someone who’s been in the trenches!
Tailor Your Application:Make sure your application speaks our language! Use keywords from the job description and relate your experiences directly to what we're building at StudySmarter. This shows us that you understand the role and are genuinely interested in joining our team.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy – just a few clicks and you’re on your way to potentially joining our awesome team!
How to prepare for a job interview at Stealth AI Company
✨Know Your Data Inside Out
Before the interview, dive deep into the data-heavy systems you've worked on. Be ready to discuss specific challenges you faced with data ingestion, modelling, and retrieval quality. This role is all about owning the data pipeline, so showcasing your experience with messy data will impress them.
✨Showcase Your Engineering Mindset
Prepare to talk about your engineering decisions, especially around hybrid retrieval and when to use different methods like BM25 or SQL. They want to see that you think critically about data quality and can make informed choices in production. Bring examples of how you've tackled these issues before.
✨Demonstrate Team Leadership Potential
Since you'll be shaping the team's culture, think about how you've led projects or mentored others in the past. Be ready to share your vision for building a strong team focused on data quality and product taste. They’ll want to know how you plan to hire and develop talent.
✨Prepare for Technical Deep Dives
Expect to get into the nitty-gritty of your previous projects. Prepare to walk them through a data-heavy system you've built, focusing on the end-to-end process. Highlight your experience with APIs, integrations, and any security measures you've implemented. This is your chance to shine!
