Coworker — Senior Software Engineer

Type: Full-time | On-site | San Francisco, CA or Atlanta, GA (preference for Atlanta) Compensation: $180K–$200K + competitive equity Hiring count: 2 Visa sponsorship: No — US citizens / Green Card holders only (not open to any visas) Reports to: Alexander Wurts, Head of Engineering

About Coworker

Coworker (coworker.ai) is a seed-stage AI startup building the AI context layer for enterprises. The platform delivers enterprise-grade chat, cowork, and code across 40+ enterprise apps (Slack, Jira, GitHub, Confluence, and more) at roughly 80% lower inference cost with equivalent output quality and no custom coding. Its core is Organizational Memory, a proprietary knowledge graph mapping how teams, tools, and information relate across a company so AI can act with full organizational context. Tasks are routed across leading models (Claude, ChatGPT, Gemini, and open-source models like Kimi) to maximize quality while minimizing cost. The company runs both an enterprise sales motion and a self-serve PLG motion, is approaching $1M ARR, and counts Webflow among its pipeline.

Founded: 2023 | Team size: ~25 (planning 6–8 more hires) | Total funding: $10M (see data note) Industry: AI, Enterprise, B2B, Software Development Website: coworker.ai Office: San Francisco, CA and Atlanta, GA (most of the tech team is in Atlanta)

Why Candidates Should Join

• First-engineer scope: One of the first engineers shaping technical architecture and engineering culture from the ground up.
• Hyper-growth trajectory: Seed-stage, expected to 10x in value next year, with real enterprise pipeline (e.g. Webflow).
• Real AI depth, not a chat wrapper: Build the context layer (knowledge graph, model routing) that makes AI useful across 40+ enterprise apps.
• Full-stack ownership: Work spans deep AI systems and traditional application code, with room to guide decisions that scale as the company grows.

Intake Call Summary

• Early-stage, hyper-growth AI company, ~20 employees at intake, planning to hire 6–8 more.
• Offices in Atlanta and San Francisco; most of the tech team sits in Atlanta.
• Hiring 2 senior software engineers, primarily Atlanta with potential SF flexibility.
• On-site: 5 days/week in Atlanta; 4 days/week in San Francisco if needed.
• Must have AI development experience and Kubernetes knowledge; Google Cloud experience preferred.
• 4–8 years of experience; strong preference for a CS degree from a reputable institution.
• Salary $180K–$200K in Atlanta, with flexibility for SF. Competitive equity, targeting ~80th percentile.
• Role open ~5 days at intake with few senior candidates in pipeline; wants to fill quickly to support growth and new client acquisitions.
• Interview process: engineering screening, two technical interviews, one to two cultural interviews; preference for on-site technical rounds with flexibility.
• Pain points: hard to find senior engineers willing to relocate to Atlanta or fit the high-impact startup culture; needs people who move fast from idea to production.
• Ideal profile: high performers from well-known tech companies wanting impact in a startup, balancing technical depth with entrepreneurial drive.

The Role

A Senior Software Engineer (4+ years) helping build the foundation for the next era of enterprise AI — a hungry, autonomous full-stack developer who thrives on ambiguity and is obsessed with making customers happy, joining as one of the first engineers at a fast-growing seed-stage startup redefining how organizations interact with AI across 40+ enterprise apps.

What You'll Be Doing

• Building and shipping across the full stack — from deep AI systems (context graphs, model routing) to traditional application code.
• Guiding early technical architecture decisions that will scale as the company grows.
• Leveraging AI aggressively in your own workflow to maximize velocity and output.
• Mentoring junior engineers and establishing the engineering culture at Coworker.
• Collaborating with the product team on vision, strategy, and roadmap while pushing the frontier of Enterprise AI.

Tech stack: GoLang, TypeScript, Python; AI/ML APIs and prompt engineering; local LLM deployment and high-volume inference; Kubernetes / unmanaged clusters; Google Cloud (preferred).

Qualifications

Seniority

• 4–8 years of experience in full-stack software engineering, building 0-to-1 in production environments [Required]

Work Experience

• Built and shipped from zero-to-one in production environments [Must have]
• AI-native development experience — Cursor / Claude Code is a strong signal [Required]
• Using AI to build more AI; personal AI projects also acceptable [Strongly preferred]

Education

• Bachelor's degree in Computer Science or related field [Required]

Hard Skills

• Experience with AI/ML APIs and prompt engineering, especially local LLM deployment and high-volume inference management [Required]
• Strong preference for Kubernetes / unmanaged cluster experience [Strongly preferred]
• GoLang, TypeScript, and Python proficiency [Strongly preferred]

Soft Skills

• Mentored/managed junior engineers, or interested in management [Required]
• Thrives with ambiguity; self-directs without detailed specs [Required]

Miscellaneous

• Based in or willing to work from SF or Atlanta [Required]

Traits to Avoid

• Needs heavy structure or detailed requirements to execute
• Resistant to using AI tools in daily engineering workflow
• Only interested in large-company, narrow-scope roles

Role Details

• Salary: $180K–$200K
• Equity: Competitive (benchmarked via Carta, 80th–90th percentile for role/city/level)
• On-site policy: In-office; 5 days/week Atlanta, 4 days/week SF; preference for Atlanta
• Visa sponsorship: None — US citizens / Green Card holders only
• Employment type: Full-time
• Location: San Francisco, CA or Atlanta, GA

Screening Questions

Collapsed in the source page ("View 6 questions to ask candidates" was not expanded). Not captured — expand and re-paste to populate this section.

Interview Process

Detailed stage names/durations were collapsed on the page ("5 steps"). Reconstructed from the intake call summary:

Stage 1 — Engineering Screening Initial engineering screen.

Stage 2 — Technical Interview On-site preferred; flexibility if needed.

Stage 3 — Technical Interview On-site preferred; flexibility if needed.

Stage 4 — Cultural Interview (1–2 rounds) Culture and startup-fit assessment.

Stage 5 — Offer Extended

Stage 6 — Candidate Hired

Ideal Companies & Backgrounds

No named-company list was present in the source HTML. The intake references high performers from well-known tech companies who want startup impact and combine technical depth with entrepreneurial drive. Expand the role page (if an Ideal Companies section exists) or paste a companies list to populate this section.

Ideal Candidate Profiles

For reference only — do not source these specific profiles.

Aurielle Perlmann — LinkedIn Senior Software Engineer | AI Engineering, Data Quality, and Integration | San Francisco, US

• Google internship and Google experience
• Open questions flagged by client: team-size context, tech-lead experience, willingness to relocate to Atlanta from New Jersey

Jake Williams — LinkedIn Engineer at Coworker.ai | Atlanta, US

• Google internship, Square/Block experience
• Exceptional technical interview: solved an open-ended coding question efficiently and explained decisions clearly
• Motivated to move into engineering management

Wontha Kyaw San — LinkedIn Tech Lead | Atlanta, US

• Strong technical skills, willing to relocate to Atlanta full-time
• Years-of-experience exception granted due to relocation willingness plus strong skills/education

Rejected Candidate Feedback

• Local/Relocation Requirement: Only consider candidates currently local to or willing to relocate to SF/ATL — remote-only profiles are a non-starter.
• True Startup 0-to-1 Experience: Candidates need external, full-time employee experience building and shipping production products (not internal or contractor-only builds).
• Hands-On AI Ops: Prioritize tangible experience in local LLM deployment and high-volume inference management — not just evaluation or AI tool usage.

Data Notes / Conflicts to Resolve

• Comp discrepancy: Salary field and intake state $180K–$200K; the "Why candidates should join" block states $160K–$200K. Using $180K–$200K (authoritative Salary field + intake). Confirm the floor.
• Total funding: Source showed a bare "10" — rendered here as $10M. Confirm.
• Collapsed sections: Screening Questions (6 candidate questions) and the detailed Interview Process stages were not expanded before copy. Re-paste with these expanded to complete the JD.