Senior Backend Engineer

Senior Backend Engineer

Location

San Mateo, CA

Hybrid — 4 days in-office per week.

Company Stage of Funding

Series A

The company has raised $73 million from leading investors, including Coatue, Kleiner Perkins, Menlo Ventures, and Madrona. It has approximately 100 employees and is experiencing rapid revenue growth, with enterprise customers already using its product.

Office Type

Hybrid — 4 days per week in-office

Salary

$250,000–$300,000 Base

The hiring team has also referenced a range of up to $320,000.

Equity

Competitive Equity

Visa

Open to visa transfers on a case-by-case basis, including H-1B transfers. TN visas are accepted. OPT candidates must have at least two H-1B lottery attempts remaining.

Employment Type

Full-time

Company Description

This Series A company is building the next generation of AI-native business intelligence, creating a new way for enterprises to interact with and understand their data.

With approximately 100 employees, the company has raised $73 million from leading investors, including Coatue, Kleiner Perkins, Menlo Ventures, and Madrona. Its product already has paying Fortune 100 customers across multiple industries, including Cisco, ConocoPhillips, Patreon, and a large private-sector bank. Revenue is growing rapidly, with the company targeting significant expansion over the coming year.

The founding team brings deep experience building and scaling enterprise technology. The CEO helped scale Rubrik, while the CTO was a founding engineer at Glean. Early engineers have backgrounds at companies such as Rubrik, Meta, Google, and Uber.

The company is looking for a Senior Backend Engineer to join its founding engineering team and help build a category-defining AI-native business intelligence platform. This is a high-ownership role where engineers work across the codebase, build large-scale data pipelines, and collaborate directly with product, co-founders, and customers to shape the engineering roadmap.

The ideal candidate has strong backend engineering fundamentals, experience building scalable data systems, and a background in a company with a strong engineering culture. Candidates should be comfortable working in a fast-paced environment, solving challenging technical problems, and contributing beyond a narrowly defined backend role.

What You Will Do

1. Build & Scale Backend Systems

• Design, build, and maintain scalable backend systems that support the company's AI-native business intelligence platform.

• Build and scale large-scale data pipelines for latency-critical analytical workloads.

• Develop reliable systems capable of processing and serving complex enterprise data workloads.

• Design cost-efficient, secure, and highly scalable systems on modern cloud infrastructure.

• Identify performance bottlenecks and improve the reliability, efficiency, and scalability of backend services.

• Write clean, maintainable, production-quality code.

• Make thoughtful engineering decisions that balance performance, cost, security, and maintainability.

• Contribute to the architecture and implementation of systems that support rapidly growing customer demand.

• Work across the backend codebase rather than focusing on a narrowly defined service or subsystem.

2. Own Product & Engineering Execution

• Take ownership of backend projects from problem definition through design, implementation, testing, and deployment.

• Work across different parts of the codebase and product as business and customer needs evolve.

• Collaborate with product and engineering teams to identify technical requirements and deliver solutions.

• Contribute to technical design discussions and help determine the direction of the engineering roadmap.

• Make pragmatic decisions in a fast-moving environment where priorities may change.

• Identify opportunities to simplify systems, improve developer productivity, and reduce technical complexity.

• Take responsibility for the quality and reliability of shipped features.

• Help establish engineering practices and technical foundations as the company continues to scale.

3. Build Large-Scale Data Pipelines

• Design and implement data pipelines that support analytical workloads at scale.

• Build systems that efficiently process and move data while meeting latency and reliability requirements.

• Identify bottlenecks in data ingestion, processing, and delivery.

• Improve pipeline performance, efficiency, and fault tolerance.

• Work on the backend infrastructure required to support AI-native analytics and enterprise business intelligence.

• Ensure systems are designed to handle complex data workflows and evolving customer requirements.

• Collaborate with other engineers to improve data processing architecture and system reliability.

• Apply strong engineering judgment to optimize performance and maintainability across data-intensive systems.

4. Collaborate With Founders, Product & Customers

• Work directly with co-founders and product teams to define product direction and engineering priorities.

• Collaborate with customers to understand their requirements and translate them into technical solutions.

• Participate in discussions that shape the product and engineering roadmap.

• Communicate technical trade-offs and implementation approaches clearly.

• Partner with cross-functional teams to deliver features that address real enterprise needs.

• Use customer feedback to identify product gaps and opportunities for improvement.

• Balance immediate product requirements with longer-term architectural considerations.

• Contribute to a collaborative engineering culture built around ownership, execution, and customer impact.

5. Shape the Engineering Culture

• Help establish engineering standards and practices as part of an early-stage engineering team.

• Contribute to technical architecture, code quality, and system design decisions.

• Bring strong engineering judgment to ambiguous and complex problems.

• Help build systems that can scale with the company's rapidly growing customer base.

• Collaborate with engineers from strong technical backgrounds to solve challenging problems.

• Take initiative in identifying areas for technical improvement.

• Contribute to a culture of high ownership, fast execution, and continuous learning.

• Help shape the technical direction of a product positioned to redefine enterprise business intelligence.

Ideal Candidate Background

Experience Requirements

• 4+ years of experience as a Backend Engineer.

• Experience in product, platform, or infrastructure engineering.

• Experience building or working on large-scale data pipelines.

• Background at companies with strong engineering cultures is a dealbreaker.

• Relevant company examples include Ramp, Brex, and DoorDash.

• A strong engineering background at reputable technology companies is preferred.

• Experience working on scalable, production-grade backend systems.

• Experience contributing across multiple parts of a codebase rather than working in a narrow technical silo.

• Comfortable working in a fast-paced, high-ownership environment.

• Startup or early-stage company experience is a plus.

• Ability to work in the Bay Area, either locally or by relocating to San Mateo.

Education Requirements

• Bachelor's degree in Computer Science, Electrical Engineering, Physics, Statistics, or Mathematics from a top-tier university — dealbreaker.

• Strong technical academic backgrounds are preferred.

• Education should be considered alongside the candidate's engineering experience and company background.

• Candidates should demonstrate strong analytical and problem-solving fundamentals.

Technical Requirements

• Proficiency in Python and TypeScript.

• Strong backend software engineering fundamentals.

• Experience building and maintaining production systems.

• Experience designing and implementing large-scale data pipelines.

• Experience in product, platform, or infrastructure engineering.

• Understanding of scalable system design and backend architecture.

• Ability to reason about latency, reliability, performance, and cost.

• Experience building secure and efficient systems on modern cloud infrastructure.

• Strong coding, debugging, testing, and problem-solving skills.

• Ability to work across a broad codebase and contribute to different areas of the product.

• Rust is part of the technology stack and may be relevant to the team's engineering environment.

Backend & Data Engineering Requirements

• Experience designing, building, or maintaining data-intensive backend systems.

• Understanding of data processing and pipeline architecture.

• Ability to build systems that support latency-critical analytical workloads.

• Experience identifying and resolving performance bottlenecks.

• Ability to design reliable and scalable data flows.

• Strong understanding of production system reliability and maintainability.

• Ability to balance system performance, operational complexity, and infrastructure cost.

• Experience contributing to platform or infrastructure improvements.

• Ability to support complex enterprise product requirements through backend engineering.

Engineering Culture & Ownership Requirements

• Experience at a company known for strong engineering standards.

• Ability to take ownership of projects from design through deployment.

• Comfortable working directly with founders and product teams.

• Ability to make sound technical decisions in ambiguous situations.

• Willingness to work across the codebase and contribute beyond a narrowly defined role.

• Strong sense of responsibility for code quality and system reliability.

• Ability to execute quickly without compromising engineering fundamentals.

• Comfortable working in a growing company where processes and architecture continue to evolve.

• Startup experience or experience in fast-paced teams is a plus.

Soft Skills

• Strong analytical and problem-solving abilities.

• Clear communication and effective collaboration.

• High ownership and accountability.

• Ability to work effectively with engineers, product managers, founders, and customers.

• Pragmatic decision-making and sound technical judgment.

• Adaptability in a fast-paced environment.

• Willingness to learn new systems and technologies.

• Ability to balance speed of execution with long-term engineering quality.

• Collaborative approach to technical design and problem-solving.

• Comfort receiving feedback and iterating quickly.

Nice-to-Have Qualifications

• Experience at a high-growth startup or early-stage technology company.

• Experience working on AI-native products or enterprise business intelligence.

• Experience building systems for enterprise customers.

• Experience with modern cloud infrastructure.

• Experience working with latency-sensitive analytical workloads.

• Experience with Python, TypeScript, and exposure to Rust.

• Experience working across backend, platform, and infrastructure systems.

• Experience collaborating directly with founders and shaping product direction.

• Experience in teams with high engineering standards and strong technical ownership.

Compensation & Benefits

• Base salary: $250,000–$300,000, with the hiring team also referencing a range up to $320,000.

• Equity: Competitive equity package.

• Work model: Hybrid, with 4 days per week in the San Mateo office.

• Employment: Full-time.

• Visa: TN visas accepted; H-1B transfers considered case-by-case. OPT candidates must have at least two H-1B lottery attempts remaining.

• Opportunity to join a well-funded Series A company with significant enterprise traction.

• Opportunity to build an AI-native business intelligence product alongside an experienced founding team.

• High ownership across backend systems, data pipelines, and product engineering.

• Direct collaboration with co-founders, product teams, and enterprise customers.

• Opportunity to shape the engineering roadmap and technical culture at an early stage.

Why Join

• Build the next generation of business intelligence: Help create an AI-native alternative to traditional enterprise BI tools.

• Work on a product with real enterprise traction: The platform already has paying Fortune 100 customers across multiple industries.

• Join a well-funded company: The company has raised $73 million from leading investors.

• Work with a strong technical team: Collaborate with leaders and engineers with backgrounds at Rubrik, Glean, Meta, Google, and Uber.

• Own meaningful engineering work: Contribute across backend systems, data pipelines, platform capabilities, and product development.

• Shape the engineering roadmap: Work directly with co-founders and product teams on technical and product decisions.

• Solve challenging technical problems: Build scalable systems for latency-critical analytical workloads.

• Have an impact early: Help shape the architecture, engineering practices, and product direction as the company grows.