Luzid — Product Engineer

Luzid is an end-to-end agentic AI delivery platform for enterprise ERP projects, used by consulting firms like EY, KPMG, Accenture, and Deloitte to run SAP and Salesforce implementations, with live deployments at customers such as Louis Vuitton. The platform centralizes project knowledge, automates repetitive delivery work, and runs autonomous agents that monitor progress, surface risks, and execute multi-step tasks against a project's real data. The team has high talent density (heavy ex-Stanford; CEO was the youngest-ever quantum research intern at Two Sigma) and is closing a ~$22M seed.

Founded: 2024 | Team size: 15 | Total funding: ~$22M Industry: Software Development, B2B, Enterprise, AI Website: luzid.io Office: San Francisco, CA

• Real enterprise impact: ship code that sits inside live enterprise implementations run by the world's largest consulting firms, used on multi-million-dollar projects under real deadline pressure.
• Full ownership: own the full stack end to end, from data pipelines to LLM integrations, agentic workflows, and the interfaces ERP teams use daily.
• Talent density: join a small, high-bar team (heavy ex-Stanford; founders include the youngest-ever Two Sigma quantum research intern and a co-founder with a hundreds-of-millions exit).
• Comp and equity: competitive base plus above-market equity, with a seed round closing now.

• Luzid is an AI platform helping large enterprises (e.g., Coca-Cola) implement software (SAP) more efficiently; currently collaborating with EY, KPMG, and Accenture.
• Seed stage, ~$22M raised; emphasis on high talent density and technical excellence.
• Hiring multiple Product Engineers to automate SAP implementation processes; open to both fresh graduates and senior engineers with startup experience.
• Candidate bar: strong engineering fundamentals, preferably B2B / enterprise; senior roles require startup experience (ideally early-stage through scaling).
• Tech: frontend on Vercel; backend FastAPI, AWS, RDS, Postgres. Senior backend engineers must have AWS experience; others can learn it on the job.
• Ideal profile: high ambition and ownership, able to work across the whole product; prior startup experience or strong project-ownership evidence preferred.
• Comp: base $150K–$300K (higher for senior), above-market equity; onsite Mon to Thu, remote Fri.
• Timeline: immediate need for 2–3 engineers, potentially doubling the team; high priority on building a large pipeline quickly.
• Interview: initial cultural-fit interview, then technical screens and a paid work trial (flexible duration and format).
• Pain points: limited founder bandwidth for recruiting; needs a larger pipeline to hit aggressive goals.

Product Engineers at Luzid own the outcomes of their code, working on a product embedded in live enterprise ERP implementations. You bring strong fundamentals, use AI tooling as a force multiplier rather than a shortcut, and can drive a feature from zero to production on your own while making the people around you better.

• →Build across the full stack: data pipelines, LLM integrations, agentic workflows, and the interfaces ERP teams rely on daily in the field.
• →Talk directly to customers, translate their friction into something buildable, ship it, and own it through deployment and beyond.
• →Automate SAP / ERP implementation processes end to end.

• 0 to 5 years as a full-stack software engineer or product engineer [Required]

• Has worked on products or features shipped to real users (impressive internships and meaningful side projects count for new grads) [Must have]
• Has worked at a company known for a rigorous engineering bar (VC-backed startups strongly preferred) [Required]
• Experience at companies focused on B2B or ERP-adjacent products [Strongly preferred]

• C.S. degree, ideally from an exceptional program (looking for evidence of technical excellence; the bar is high) [Required]

• Fullstack capable (ideally TypeScript/React frontend, Python/FastAPI backend) [Required]
• Experience building LLM-powered features [Strongly preferred]

• Must show clear signals of ambition and high ownership (ambitious side projects, hackathons, impressive companies, etc.) [Must have]
• Has a portfolio of recent, ambitious side projects [Strongly preferred]

• Career exclusively at large, slow-moving tech companies
• Solutions Engineers or implementation-focused roles

• Salary | $150,000–$250,000 |
• Equity | 0.2–0.6% |
• On-site policy | Hybrid: in-office Monday to Thursday, remote Friday |
• Visa sponsorship | Open to transfers (OPT, H-1B); sponsors H-1B and O-1 for US-based candidates |
• Employment type | Full-time |
• Location | San Francisco, CA |

1. What's the most technically challenging thing you've worked on or spent a lot of time on that no one asked you to do?
2. Where do you see your career five years from now?
3. Do you require visa sponsorship? If so, please describe what kind.
4. From a product standpoint, what do you enjoy working on the most?
5. Can you be on-site (in-office Mon to Thu)? If not, are you willing to relocate?
6. What is your salary expectation?
7. How actively are you exploring new opportunities?

Updated Jun 24, 2026

ERP-adjacent and back-office automation DOSS.COM, Ramp, Tropic, Vendr, Numeric, Puzzle, Pilot Flying J

For reference only — do not source these specific profiles.

Amrit Baveja — LinkedIn Founding Team @ Sycamore | Stanford Alum | San Francisco, United States

• Repeat startup experience; Sycamore Labs works with enterprises
• Stanford C.S.
• Interesting side projects / research experience

Harsh Deep — LinkedIn CS + Math @ MIT | San Francisco Bay Area

• New grad, but clearly high slope and ambitious (MIT C.S., Jane Street internship, YC alum)

• Ensure all sourced candidates have clear, exceptional technical signals: evidence from high-talent, high-growth startups or elite institutions with outstanding side projects and hackathons.
• Prioritize candidates who can demonstrate solid 0-to-1 product ownership and have shipped products with real user impact, especially in B2B / ERP-adjacent environments.
• Avoid resumes from candidates with careers exclusively at large, slow-moving companies, or roles that don't reflect a founder-like, high-ownership mindset.
• Emphasize candidates with proven experience building agentic AI and LLM-powered features that integrate across the full stack, matching the exact tech stack and customer-facing needs.