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For Companies At a Glance
- Tasks: Architect and build an AI SRE agent for production incident investigations.
- Company: Early-stage startup revolutionising AI for production systems.
- Benefits: Competitive salary, equity, 30 days leave, health insurance, and team socials.
- Other info: Opportunity for high ownership and significant impact in a fast-paced environment.
- Why this job: Join a small, dynamic team and shape the future of AI in production engineering.
- Qualifications: 5+ years in software engineering with strong backend and distributed systems experience.
The predicted salary is between 70000 - 130000 £ per year.
About Us
Tracer is an early-stage, venture-backed startup building the open source AI SRE agent for production engineering. Tracer is 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.
The Role
Tracer is building an open source AI SRE agent that automatically investigates production incidents across the entire production stack. We are hiring a Founding AI Engineer (Staff) in London to own the core architecture and ship an agent that produces grounded RCAs and fix suggestions across production infrastructure. Humans stay in control of production decisions; the agent does the heavy lifting. This is a hands-on, high-ownership role at the center of the product.
Tech Stack
- Python + LangGraph (for multi-agentic alert investigation)
- Rust (systems that are fast and correct)
- ClickHouse (high-volume event + investigation history at scale)
- AWS + Terraform (infrastructure that builds itself)
- Next.js + TypeScript (front-end)
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
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 and cut what doesn’t.
Compensation & Benefits
Total Compensation Range: £70,000 – £130,000+ (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
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
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
Founding AI Engineer (Staff) employer: Tracer
Contact Detail:
Tracer Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding AI Engineer (Staff)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those connected to Tracer. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got projects or contributions on GitHub, make sure to highlight them. We love seeing real-world applications of your work, especially in AI and production systems.
✨Tip Number 3
Prepare for the interview process by diving deep into our tech stack. Brush up on Python, Rust, and AWS. The more you know, the more confident you'll feel when discussing how you can contribute to our mission.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you're genuinely interested in being part of the Tracer team.
We think you need these skills to ace Founding AI Engineer (Staff)
Some tips for your application 🫡
Show Your Engineering Skills: When you’re writing your application, make sure to highlight specific projects or products you've shipped. We want to see the evidence of your engineering prowess, so don’t just tell us you’re great—show us!
Connect with Our Mission: In your application, let us know why Tracer excites you. What about our open source AI SRE agent resonates with you? We love seeing genuine passion for the problem we’re solving, so share your thoughts!
Share Your Work: Don’t forget to include links to your GitHub, portfolio, or any other work that showcases your skills and thought process. We’re keen to see how you think and build, so make it easy for us to check out your stuff!
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
✨Know Your Tech Stack
Make sure you’re well-versed in Python, Rust, and the other technologies mentioned in the job description. Brush up on your knowledge of distributed systems and incident tooling, as these will be crucial for the role.
✨Showcase Your Experience
Prepare specific examples from your past work that demonstrate your ability to ship products quickly and effectively. Highlight any experience you have with early-stage startups, as this will resonate well with the team at Tracer.
✨Understand the Problem Space
Research the challenges faced in production engineering and AI SRE. Be ready to discuss why you’re passionate about solving these problems and how you can contribute to Tracer’s mission.
✨Prepare for Practical Exercises
Expect a take-home exercise or technical problem-solving session. Practice similar exercises beforehand to ensure you can showcase your skills effectively during the interview process.