At a Glance
- Tasks: Lead the development of AI systems for production data pipelines and turn alerts into actionable insights.
- Company: Join Tracer, a cutting-edge startup revolutionising AI for enterprise software.
- Benefits: Competitive salary, equity options, 30 days leave, health insurance, and team socials.
- Other info: Work closely with founders and enjoy excellent career growth opportunities.
- Why this job: Be at the forefront of AI innovation and make a real impact in a dynamic environment.
- Qualifications: 5+ years in software engineering with strong backend and distributed systems experience.
The predicted salary is between 150000 - 220000 € per year.
About Us
Tracer is an early-stage, venture-backed startup building autonomous AI agents for production data pipelines. We are backed by experienced operators and investors who believe AI for production systems will be one of the defining enterprise software categories of the next decade. Our team is small, senior, and highly execution-focused.
About the Role
Tracer is building agentic alert investigation for production data pipelines. We’re hiring a Lead AI Software Engineer in London to own and build the core agentic systems that turn production alerts into grounded RCAs and fix suggestions for a small set of high-value alerts. Humans stay in control of production decisions, the agent does the heavy lifting. You’ll be the technical point of ownership for this system, working closely with the founders while remaining deeply hands-on.
You’ll Love Our Tech Stack
- Python + LangGraph (for multi-agentic alert investigation)
- Rust (because we like systems that are fast and correct)
- ClickHouse (high-volume event + investigation history at scale)
- AWS + Terraform (infrastructure that builds itself)
- Next.js + TypeScript (because front-end should be sexy too)
What You’ll Do
You’ll own the core systems that turn an alert into a defensible investigation and RCA. In practice, you will:
- Architect and build the core alert, investigation, root cause analysis (RCA) pipeline in Python
- Design and implement key systems including:
- Alert ingestion + normalization
- Context enrichment + correlation
- Problem framing outputs
- Hypothesis orchestration engine
- Investigation execution runtime
- Investigation artifacts + reporting
- Lead core architecture decisions and ensure the system is observable, auditable, and reliable from day one
- Partner with founders to ship a small set of high-value alert types that work extremely well, then expand coverage deliberately
- Build customer-ready integrations across the pipeline stack
- Set a high bar for technical quality, speed, and pragmatism as the team grows
What We’re Looking For
- 5+ years (ideally 10+) professional software engineering experience.
- Proven track record of shipping real products at high velocity
- Strong backend and distributed-systems foundations, ideally with experience in data platforms and production pipeline stacks and incident/observability tooling.
- Experience working at an early-stage startup and bonus points for having joined earlier.
- High ownership and sharp product instincts: you build what matters, cut what doesn’t, and take responsibility for outcomes.
Compensation & Benefits
Total Compensation Range: £150,000 – £220,000+ (salary and equity value). We structure compensation as follows:
- Competitive base salary
- Meaningful equity ownership with real upside
- Final package depends on experience, impact, and seniority
What’s included:
- Salary + equity (equity typically ~0.3% – 2%+)
- 30 days annual leave
- Employee health insurance
- Visa sponsorship
- Weekly team dinners and socials
- Regular team offsites and trips (our most recent was Kenya)
- The satisfaction of building a world-class AI-powered product with an exceptional team
Application Requirements (Read Carefully)
We are intentionally selective. Please answer all of the following in your application. Applications that do not include these will not be reviewed.
- Why do you consider yourself an exceptional engineer? (Be specific, we’re interested in evidence, not adjectives.)
- Why Tracer?
- What about this problem, product, or moment resonates with you?
- Links we should see: GitHub, Portfolio, blog posts, talks, or anything else that shows how you think and build
Our Recruitment Process
- Introductory Call (15-30 mins): Call with our hiring manager to discuss your background, motivations, and learn more about Tracer
- Role Fit Interview (45 mins): Meet with your manager or a similar-level team member to review your working style, skills, and fit for the role
- Take-home & Competency Deep Dive (1 hour): Complete a practical exercise (e.g., case study, presentation, or technical problem-solving) to explore the role's responsibilities and expectations
- On-site meetup (Half Day): On-site interviews and team lunch at our headquarters to ask any questions and experience our office and culture firsthand
- Offer: Final decision and offer
Lead AI Software Engineer employer: Tracer Cloud Inc
At Tracer, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture in the heart of London. Our team enjoys competitive compensation, meaningful equity ownership, and a generous 30 days of annual leave, alongside regular team-building activities and offsite trips that enhance collaboration and camaraderie. As a Lead AI Software Engineer, you'll have the unique opportunity to shape cutting-edge technology while working closely with experienced founders, ensuring your professional growth and impact in the rapidly evolving field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Software Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in your industry, especially those at startups. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those relevant to AI and data pipelines. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to the role. We want to see how you think on your feet, so get comfortable explaining your thought process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team at Tracer.
We think you need these skills to ace Lead AI Software Engineer
Some tips for your application 🫡
Show Your Engineering Skills:When answering why you consider yourself an exceptional engineer, be specific! Share concrete examples of projects you've worked on, challenges you've overcome, and the impact your work has had. We want to see the real you in action!
Connect with Our Mission:In your application, make sure to explain why Tracer excites you. What about our mission to build autonomous AI agents resonates with you? Show us that you’re not just looking for a job, but that you genuinely care about what we’re doing.
Highlight Relevant Experience:Don’t forget to include links to your GitHub, portfolio, or any other relevant work. This is your chance to showcase how you think and build. We love seeing your past projects and how they relate to the role!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Tracer Cloud Inc
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, especially Python, Rust, and AWS. Be ready to discuss how you've used these tools in past projects and how they can apply to building autonomous AI agents.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex problems in software engineering. Highlight your experience with incident/observability tooling and how you’ve contributed to high-velocity product shipping.
✨Demonstrate Ownership and Impact
Be ready to share instances where you've taken ownership of a project or feature. Discuss how your decisions led to measurable outcomes, showing that you understand the importance of building what matters.
✨Engage with the Founders' Vision
Research Tracer and its mission. Prepare thoughtful questions about their approach to AI in production systems and express why this resonates with you. This shows your genuine interest and alignment with their goals.
