Lead AI Software Engineer

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.

1. Why do you consider yourself an exceptional engineer?
   (Be specific, we’re interested in evidence, not adjectives.)

2. Why Tracer?
   What about this problem, product, or moment resonates with you?

3. 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