S
SonarSource
Software Engineer (Agentic Code Review, Gitar)
Skills
AI
2 months ago
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Important information
Contract type:
Permanent
Location:
San Mateo, CA, USA
Work mode:
Onsite
Published on:
20 August 2026
What they need
- We are looking for a Software Engineer to join the team building Gitar’s core platform
- Gitar is building an AI-native code validation platform that automates the entire pull request lifecycle
- We review every change with full awareness of the codebase, team conventions, and the intent behind the code; we generate fixes, validate them against CI, and only consider the work done when the build passes; and we automate the full pull request lifecycle from creation to merge
- You will work at the intersection of program analysis, developer tools, and AI, helping design and ship systems that reason about code at depth
- You will do so by combining static and dynamic analysis with large language models to catch bugs that rules-based tools miss, generate validated fixes, and automate the developer’s workflow end to end
- Design and build program analysis systems that reason about code at the level of intent, control flow, data flow, and behavior, across languages and at the scale of thousands of repos and large monorepos
- Combine static and dynamic analysis with large language models to detect functional bugs, logic errors, and behavioral issues that deterministic tools cannot catch
- Build the AI agents and orchestration layers that review pull requests, generate and validate fixes against CI, root-cause CI failures, and automate the full pull request lifecycle from creation to merge
- Develop indexing, retrieval, and embedding systems that give models the right context (codebase, conventions, dependencies, and intent) at the right cost and latency
- Own the production characteristics of the systems you build: correctness, accuracy, latency, cost, observability, and security in a zero-trust environment
- Partner with the SonarQube team to deepen the integration between deterministic static analysis and AI-native validation, building workflows where one informs the other
- Engage directly with customers, many of whom run the largest engineering organizations in the world, to understand their workflows and ship what they need
Benefits
- 401K Plan: Sonar US matches up to 4% of gross salary
- 90% healthcare premium coverage for employees, 60% for dependents
- EAP (Employee Assistance Program) Health Savings Accounts (HSA, FSA, DCFSA). Supplemental coverage is offered by EE’s expense
- Life and disability insurances fully paid by Sonar. Sonar covers 100% of Telemedicine for FTE whom are covered by Sonar medical
- Pet Insurance
- Hospital Indemnity, Accident, Critical Illness
- Time Off: 25 PTO days plus additional days based on seniority and circumstances
- Commuting: Public transport reimbursement of 60% for annual subscription
- Free parking space
- Pension: Sonar UK contributes 50% of the total costs, which amounts to 5% of your gross salary for saving. Employees contribute the other 5%
- Flexibility to work from home 2 days a week on Wednesdays and Fridays
- Health Insurance: Sonar covers 100% of the employee premiums for medical, dental, and EAP (Employee Assistance Program) plans through BUPA
- Time Off: 28 PTO days, plus additional days based on seniority and circumstances
- Commuting: we will reimburse 60% towards the cost of an annual public transport pass- 2–4 years of professional software engineering experience
- Exposure to or strong interest in program analysis fundamentals: static analysis, dynamic analysis, type systems, intermediate representations, control- and data-flow analysis, or symbolic execution
- Strong written and verbal communication, comfort working directly with sophisticated engineering customers, and the judgment to make trade-offs across correctness, latency, cost, and developer experience
- Have practical, hands-on experience with AI and LLM-driven development
- A PhD or MS in Computer Science (or equivalent experience)
- Solid engineering fundamentals: data structures, algorithms, and the ability to reason about correctness and performance
- Experience building developer tools that engineers actually use: compilers, build systems, IDE tooling, linters, refactoring tools, test infrastructure, or large-scale code transformation
- Experience in industry research labs (e.g., Microsoft Research, Google Research, Meta AI), at large-scale developer infrastructure teams (Uber, Google, Meta, Microsoft, Stripe, etc.), or as a contributor to widely used open-source compilers, analyzers, or developer tools
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