freehire launches on Product Hunt on 26 August.

Follow →

Rama — Founding Engineer

Summary

Rama is a startup building an AI-powered operating system for the electronic components supply chain. As a founding engineer, you will own product streams end-to-end, build robust data pipelines for legacy ERP systems, and work directly with customers using Python, TypeScript, and AI-native development tools.

Rama — Founding Engineer

Type: Full-time | On-site | Sansom Street, San Francisco, CA Compensation: $165K–$190K base + meaningful early-stage equity Hiring count: 2–3 Visa sponsorship: Yes — open to transfers (OPT, H1B) and new sponsorships (new H1B, TN) Reports to: Aidan Holmes, Co-founder / CTO

About Rama

Rama is building the AI-powered operating system for the $3T electronic components supply chain. It's live in production with top-10 independent distributors, processing hundreds of millions in component transactions annually, with growth accelerating through word-of-mouth.

Founded: 2025 | Team size: 5 | Total funding: $4M ($3M+ seed led by Wischoff Ventures; participation from Liquid 2, Stage 2, Rebellion VC, Entrepreneur First) Industry: AI, B2B, Data, Enterprise, Logistics, Software Development Website: tryrama.com Office: San Francisco, California (Sansom Street)

Why Candidates Should Join

  • $3T+ market with real traction: Live in production with top-10 independent distributors processing hundreds of millions in component transactions annually; growth accelerating through word-of-mouth.
  • Well-funded and investor-backed: $3M+ seed round led by Wischoff Ventures with participation from Liquid 2, Stage 2, Rebellion VC, and Entrepreneur First.
  • Exceptional founding team: CTO was the first AI hire at an a16z-backed startup; co-founder has a deep manufacturing background; VP Sales scaled a YC company from $500K to $30M in revenue.
  • True founding engineer ownership: Own your product streams and customer relationships from week one, with a clear path to leading your own engineering team as the company scales.

Intake Call Summary

  • Electronic component distribution startup; ~5 team members with plans to expand. SF-based; founders returning to the US after securing O1 visas.
  • Hiring 2–3 founding engineers to replace an outgoing member and support growth; wants both generalist and data-engineering strength, with a real need for robust data pipelines.
  • Candidate bar: 1–3 years of experience or equivalent GitHub evidence; startup or competitive backgrounds preferred.
  • Comp: $165K–$190K + significant equity. 5 days/week in-person in SF, with potential remote flexibility during visa processing. Visa sponsorship available; slight preference for UK candidates for easier referencing.
  • Moving fast — some candidates already in second-stage interviews. Four-stage evaluation including a paid work trial.
  • Flat structure: engineers report directly to the CTO/co-founder. Culture is collaborative and intense but light-hearted.
  • Tech: SQL, Python, TypeScript preferred, with flexibility for adaptable engineers. Emphasis on building/maintaining data pipelines and customer-facing skills.
  • Ideal profile: competitive nature (evidenced by non-work achievements) and strong communication skills for interacting with non-technical customers.
  • Pain points: legacy systems requiring innovative integration solutions; balancing customer demands against technical development.

The Role

Founding Engineer joining as one of the first engineers at a high-growth startup building the AI-powered OS for the $3T electronic components supply chain. You'll work directly with the CTO, own entire product streams from day one, and build the data infrastructure that powers pricing intelligence for some of the world's largest distributors.

What You'll Be Doing

  • Building and hardening robust data pipelines that process live production data from legacy ERP systems (some installed in the 90s) for customers doing $100M+ in annual revenue
  • Owning your own product stream end-to-end — from customer conversations to shipped features — within your first two weeks
  • Deploying and customizing data ingestion tools across multiple customers with different file formats, ERPs, and integration requirements
  • Communicating directly with non-technical customers (typically 40s–60s) to learn the industry and gather requirements
  • Contributing to AI agent development including voice AI applications and LLM-powered data ingestion as the foundational data layer matures

Tech stack: Python, TypeScript, SQL, .NET, AI Agent SDKs, Claude Code, Cursor, Codex

Qualifications

Seniority

  • 1–5 years of experience in full-stack or backend engineering (Python and TypeScript) [Required]

Work Experience

  • Shipped backend systems in production: SaaS, services, or data infrastructure [Must have]
  • Evidence of high slope: promoted early, or built side projects / open source (visible on GitHub or personal site) [Required]
  • Experience at high-bar startups or companies [Strongly preferred]
  • Built data pipelines or integrations with legacy systems (ERP, EDI) [Strongly preferred]

Education

  • Degree in a quantitative / problem-solving field (CS, physics, math, engineering) [Required]

Hard Skills

  • Experience building or maintaining data pipelines at scale [Must have]
  • Proficient in Python and TypeScript [Required]
  • AI-native developer, actively uses AI coding tools (Cursor, Claude Code, Codex) and has opinions on them [Strongly preferred]

Soft Skills

  • Can explain technical concepts clearly and concisely to non-technical users [Required]

Miscellaneous

  • Evidence of high-level competitiveness outside engineering (D1 athlete, martial arts belt, music at highest grades, etc.) [Strongly preferred]

Traits to Avoid

No dedicated "Traits to Avoid" section was present in the source role page. The closest equivalent is the Non-ideal Companies list under Ideal Companies & Backgrounds.

Role Details

  • Salary: $165K – $190K
  • Equity: Meaningful early-stage equity (competitive)
  • On-site policy: 5 days/week in-office, Sansom Street, San Francisco
  • Visa sponsorship: Open to transfers (OPT, H1B) and new sponsorships (new H1B, TN)
  • Employment type: Full-time
  • Location: San Francisco, CA

Screening Questions

  1. Are you able to work in San Francisco and come into the office 5 days per week?
  2. Share a link to your GitHub profile or a project you've built that has real users.
  3. Can you be on-site? If not, are you willing to relocate?
  4. What is your salary expectation?
  5. How actively are you exploring new opportunities?

Interview Process

Stage 1 — Submit candidate After submission, you'll be notified if the hiring manager wants to proceed.

Stage 2 — Initial Screen with Aidan, CTO (20 min) Culture-fit and vibe-check call with Aidan Holmes (CTO/co-founder). Not a technical assessment — focus is on team fit, clear communication, and personality. High pass rate; filters out candidates who'd struggle in customer-facing situations or wouldn't mesh with the collaborative, light-hearted culture.

Stage 3 — Technical Interview: GitHub Project Deep Dive with Aidan, CTO (60 min) Candidate selects a GitHub project and sends it in advance. Opens with a 20-minute demo/presentation (also assesses customer-facing communication), followed by 40 minutes of deep technical questioning. The team reviews the code beforehand and probes whether the candidate truly understands what they built, the trade-offs made, and their personal contributions — regardless of whether AI tools were used.

Stage 4 — Technical Assessment: Debugging AI-Written Code (40 min) Live 40-minute assessment on a Claude Code–generated codebase with intentional bugs. Candidate reads, identifies, and fixes the bugs, and is encouraged to use AI tools. Evaluates their ability to understand/debug AI-written code and how systematically they use AI coding tools. May be skipped for candidates the team is particularly bullish on.

Stage 5 — Paid Work Trial (1 day) One-day paid trial working alongside the team on real tasks — the final evaluation of engineering ability, collaboration, speed, and communication. Ideally in-person in SF (or the EF office if founders aren't yet back in the US); remote arrangements possible depending on visa/logistics.

Stage 6 — Offer Extended

Stage 7 — Candidate Hired

Ideal Companies & Backgrounds

Updated Jul 30, 2026

Horizontal distribution / supply chain tech startups (10–50 people) Endeavor, Flexport, project44, FourKites, Fictiv, MacroFab, Cofactr, Luminovo, Octopart

High-growth startups (10–50 people) with strong data pipeline and B2B infrastructure focus Fivetran, Airbyte, Dagster Labs, Prefect, Hightouch, Census, Supabase, Retool, Temporal Technologies

YC-backed early-stage startups where engineers ship production software end-to-end Supabase, Vercel, Railwaymen, Render, Resend, Trigger.dev, Inngest

Non-ideal companies — do not source from these Companies backed by Entrepreneur First (EF) — founders know these teams personally: Tractable, Cleo, Permutive, Onfido, Rotate, Jitsu, Synthesia, Magic Pony Technology

Data note: The "High-growth startups" list is labeled "Show all 10 companies" but only 9 were expanded in the source HTML — 1 company is missing. A separate one-item "Ideal Companies" group (Endeavor) also appeared, likely a duplicate/miscategorized entry. Please provide the full list.

Submission Standard — What Good Looks Like

The client has surfaced three reference profiles (two highlighted "great fit" candidates plus their actual first hire). Read together, the bar is best treated as an OR, not an AND — a strong candidate clears it via either archetype:

  • Archetype A — Pedigree + competitiveness: a brutal-hiring-bar "badge" employer (Google, Amazon, DRW, top quant/HFT) plus elite competitiveness outside engineering (D1 athlete, national record, black belt, chair of a major society). Bera and Adit fit this.
  • Archetype B — Scrappy end-to-end builder: a non-traditional path with clear 01 ownership, production shipping into messy/external systems, and genuine customer-facing ability. Rodrigo (the first hire) fits this — no CS degree, no badge employer, but real integration work (YC) and years of direct customer/sales experience.

Scoring implications:

  • Customer-facing communication is an elevated, top-tier screen signal — not a nice-to-have. The role is heavily customer-facing (non-technical distributors, 40s–60s), it's the JD's Required soft skill, and it recurs in rejected-candidate feedback. Rodrigo's hire confirms the client will trade pedigree for a builder who can own customer relationships.
  • The Education "Required" and experience floor are satisfiable via demonstrated building. The intake call allows "equivalent GitHub evidence," and Rodrigo was hired without a CS degree. Strong, verifiable shipping evidence can clear the gate — flag a non-traditional path for judgment rather than auto-rejecting. (Confirm with David before treating this as settled.)
  • Absence of Archetype-A competitiveness/badge is not a penalty when Archetype B is clearly met, and vice versa.

Ideal Candidate Profiles

For reference only — do not source these specific profiles.

Bera Ajala — LinkedIn Quantitative AI Engineer | Prev. SWE @ Google & Amazon | UMich D1 NCAA Track & Field | Scottish Athletics Junior Record Holder | United States

  • Competitiveness (top signal): D1 Track & Field, University of Michigan — 6x All Big 10, #2 in school history, 2x NCAA Regional Qualifier, national junior record holder
  • Badge employers: prior SWE at Google & Amazon; now AI Engineer at OneStream (Xperiflow team — AI/ML implementation, quantitative analysis)
  • Education: BS Computer Science, University of Michigan (2024) — strong quantitative degree from a top school
  • Self-driven initiative: co-founded "Michigan Athletes In Tech"; VP / Head of Professional Development at ColorStack; Investment Analyst at BlackGen Capital
  • ~1 yr full-time post-grad — inside the 1–3 year sweet spot

Adit Kulkarni — LinkedIn Building Agents | Ex Quant | United Kingdom

  • Domain-exact founder: currently founding a stealth AI startup building agents for electronic components — Rama's exact space
  • Voice AI builder: SaraSpeak — voice-first AI language tutor, sub-1s latency, NLP pipelines, LLM-judge prompt optimization, Python/FastAPI + native iOS; 110 organic beta installs
  • Badge + competitiveness: Quantitative Trader at DRW for ~5.9 yrs (Global Delta One, Sharpe 5); JPM summer analyst (turned down return offer); Co-Chairman of Warwick's largest society (2,500+ members)
  • Education: MSc Data Analytics, Imperial College London; BSc Economics, Warwick
  • So strong that a full interview round was skipped

Previous Hire — Fit Benchmark

Not for sourcing — reference for what a successful hire has actually looked like.

Rodrigo Tari — Founding Engineer @ Rama (Feb–Jun 2026), the client's first engineering hire; since co-founded Alfera.

  • Archetype B exemplar: non-traditional path — 42 (project-based software school, no CS degree) + EHL (International Business); earlier years in wine sales and hospitality
  • Real 01 / integration chops: Backend Engineer (contractor) at Stacksync (YC W24) — shipped production API connectors (Shopify, Teams, Crustdata, Hyperline); directly analogous to Rama's ingestion/integration work
  • Customer-facing depth: BD / sales at Dealroom (full sales cycle with VP BD and COO); years of direct customer selling
  • Takeaway: confirms the client will hire a scrappy, customer-capable builder without pedigree or a formal CS degree — the strongest evidence for weighting Archetype B and customer-facing ability heavily

Rejected Candidate Feedback

  • Ensure candidates demonstrate hands-on ERP / legacy-system integration experience, not just generic data pipelines.
  • Candidates must show clear customer-facing communication skills, with examples of translating technical concepts for non-technical users.
  • Emphasize evidence of end-to-end production ownership (from requirement gathering to shipping features) in portfolios or GitHub.
  • Prioritize applicants with a high-slope signal (side projects, open-source creds, competitive extracurriculars) that differentiates them from standard early-stage hires.

See also

Tailor your CV for this role?

We couldn't check your fit for this role — add a CV to your profile to see it next time.

A new version of freehire is available