# Lead Software Engineer - Backend at Faros AI

> Hybrid · United States · Staff · Backend · open. Source: https://alderhq.app/jobs/ashby%3Afaros-ai%3A0a856ddc-76d5-4cbe-bcfa-b0a5ac928b2e (read 2026-11-07).

## Facts (observed)

- Company: [Faros AI](https://alderhq.app/companies/faros-ai)
- Location text: Redwood City
- Where it can be done from (inferred): Hybrid · United States (evidence: "Location: Redwood City")
- Posted: 2026-10-02 (35 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-03
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/faros-ai/0a856ddc-76d5-4cbe-bcfa-b0a5ac928b2e
- Skills listed (inferred): TypeScript, JavaScript, Node.js, Python, GraphQL, AWS, GCP, Azure, Docker, SQL

## Pay and sponsorship

- Posted pay: $210k–$250k per year (from the listing's pay field)
- Market band for similar posted roles (SF Bay Area, n 80): p25 $221k, median $244k, p75 $260k

## Description (the employer's text)

### Mission

At Faros AI, we are reshaping the way engineering organizations operate, with an engineering intelligence platform that provides visibility and context across the organization's software delivery systems. This deep operational context supports engineering leaders today, and is increasingly essential as AI agents begin to operate within real software delivery environments. Faros AI is laying the foundation for how humans and AI will build software together in the years ahead.

### About the Role

We’re looking for software engineers who want to build the future of engineering operations with us. This is a hands-on role. While you will drive architectural vision and mentor senior engineers, you will spend a significant portion of your time writing code, building core systems, and solving our most complex technical challenges.

### Responsibilities

Architect, build, and scale our highly scalable data infrastructure and core engineering platforms, owning the hardest technical problems from whiteboard design all the way through to production deployment.

Lead from the front by writing high-quality, resilient code, establishing architectural standards, and building best practices for backend services/APIs to ensure system-wide reliability, security, and scalability.

Act as a technical partner to product and engineering leadership, translating business strategy into technical roadmaps and mentoring other engineers.

### Baseline Requirements

### Experience

5–8+ years with ownership of critical components or services

### Technical Stack

Expert-level proficiency in TypeScript + Node.js and/or Python

Experience designing/consuming/implementing REST/GraphQL APIs

Experience with building & productionizing web services, data pipelines, ETL/ELT, orchestration frameworks

Strong database fundamentals (SQL/NoSQL)

CI/CD familiarity (GitHub Actions, CircleCI, etc.)

Experience running production workloads including monitoring, alerting, logging, metrics, traces, oncall

Security fundamentals

### Cloud

Hands-on experience with one of more major cloud providers: AWS, Azure, GCP (certifications are a plus)

### Collaboration & Communication

Comfortable working with distributed international teams

Strong ability to communicate complex technical trade-offs to non-technical stakeholders

### English

English C1: able to participate in technical calls and write clear communication.

### Education

Degree in Computer Science / Software Engineering, or equivalent real-world experience.

### Nice-to-Haves

Experience with building & integrating with SaaS platforms

Experience with engineering analytics or developer-productivity tooling

Experience with IaC, containers, serverless, queues/event-driven architectures

Experience with security practices (authN/authZ, secrets management)

Familiarity with engineering metrics (DORA, code quality, delivery metrics)

Hands-on experience using coding agents (AI-assisted development)

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Afaros-ai%3A0a856ddc-76d5-4cbe-bcfa-b0a5ac928b2e and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.