Giga — Staff Backend Engineer

• →Jun 15, 2026: Avoid healthcare tech at large — pharma, biosciences, healthcare-related manufacturing, etc. Prefer candidates from more apples-to-apples industries.
• →May 29, 2026: All submissions must already be located in the Bay Area. No candidates who need to relocate. Candidates must be close enough to the Dogpatch SF office that 5 days/week on-site is realistic and sustainable.
• →May 26, 2026: The hardest onsite round is a 2.5-hour AI agent-building build session under time pressure. Candidates comfortable with AI coding tools perform better. The team also wants candidates genuinely excited about a startup environment — strong technical candidates from larger companies sometimes lose momentum if hesitant about a smaller team.
• →Sep 10, 2025: Salary band $150K–$350K — $250K cap for engineers with <5 years experience, $350K cap for 5+ years. Interviews are Python-heavy and move fast; best fits adapt in unstructured environments and move quickly.

• →System architecture: Design how Giga's agent infrastructure evolves as it scales, making tradeoffs between speed, reliability, and complexity.
• →Hard technical problems: Own the most ambiguous, highest-stakes projects where getting it wrong would hurt the business.
• →Technical strategy: Identify gaps in systems before they become problems and build the case for addressing them.
• →Engineering quality: Set standards for code review, system design, and operational excellence through your own work, and mentor other engineers via collaboration on real work (not formal management).

A staff engineer to help shape the technical direction of Giga's backend systems — leading complex projects, making platform-wide architectural decisions, and raising the bar for engineering quality. This is a build role, not an advisory one: you write code, own systems, and ship, while also identifying what the team should build next and how.

• 7–15 years of experience in backend/infrastructure engineering, with Python and distributed systems [Required]

• Clear promotion trajectory (e.g. L4L6 in 6–7 years) [Must have]
• Experience at high-growth SaaS startups or top-tier tech (Meta, Netflix, Stripe, Snap, Uber preferred) [Required]
• Experience independently owning and driving initiatives to completion without oversight [Required]

• CS, Math, or Stats degree from a top university globally [Strongly preferred]

• System design expertise for scalable, reliable backend platforms [Required]
• Python backend development (Django/FastAPI) [Required]
• Uses AI coding tools (Cursor or Claude) actively [Strongly preferred]

• Must work on-site 5 days/week in San Francisco, and must already be located locally — not interested in candidates who need to relocate [Must have]
• Currently at or recently promoted to staff level (L6/E6 equivalent) [Required]

• No slope: stagnant at the same level for 5+ years
• Pure architect/manager who no longer writes production code
• Legacy company lifers (Cisco, IBM, Oracle, banks, Salesforce)

• Healthcare tech — current or recent employer in healthcare tech at large (pharma, biosciences, healthcare-related manufacturing). (Client instruction, Jun 15, 2026.)
• Location / relocation — candidate must already be located within Bay Area driving distance of the Dogpatch SF office, sustainable for 5 days/week on-site. Willingness to relocate does not satisfy this. This overrides the standard rule that applying implies willingness to relocate. (Client instruction, May 29, 2026.)

Updated May 29, 2026

Ideal Companies Facebook, University of Waterloo, Meta

High-Slope Big Tech (Strong Infrastructure & Talent) Netflix, Stripe, Lyft, Snap Inc., Pinterest, Uber, DoorDash, Airbnb

High-Growth SaaS & Product-Led Startups Figma, Datadog, Snowflake, Notion, Brex, Databricks, Airtable, Miro, Rippling

AI-Native & Infrastructure Companies Cohere, Vercel, OpenAI, Modal Labs, Perplexity AI, Anthropic, Scale AI, Hugging Face

Legacy Enterprise & Hardware IBM, HP, Dell Technologies, Oracle, Cisco, Salesforce, Broadcom, SAP, VMware

Large Tech with Perceived Talent Stagnation (unless high slope is evident) Microsoft, Google, Amazon, LinkedIn, Apple, Yahoo

Traditional Banking & Financial Services Capital One, Morgan Stanley, Goldman Sachs, Bank of America, JPMorgan Chase, Wells Fargo, American Express

Avoid Companies DFINITY Foundation, Stealth Startup, NVIDIA

Also avoid: healthcare tech at large (pharma, biosciences, healthcare-related manufacturing).

For reference only — do not source these specific profiles.

Thien Nguyen — LinkedIn I craft stories in code and diagrams. | San Francisco Bay Area

• Meta + Snap experience — both preferred companies
• Sebastian could backdoor reference check via Snap network
• AI startup experience at Kardia Labs
• Area for improvement: if not producing code, not a fit
• Note: need to verify coding involvement

Austin Mease — LinkedIn Software Engineer focusing on generative AI and latency. Passionate string manipulator | San Francisco, United States

• Roblox Hippocratic AI trajectory shows strong backend + AI experience
• Staff-level at an AI startup — relevant domain

Jonathan Huang — LinkedIn Staff Software Engineer | San Francisco Bay Area

• High slope in big tech + experience at Netflix
• CS degree from Stanford

• Sourcing candidates with a high slope and proven startup-style progression is critical — avoid those stagnant at large, slow-moving companies.
• Ensure candidates demonstrate strong hands-on coding and concrete production contributions, not just managerial or architect roles.
• Reconfirm candidates are locally based in SF or fully committed to on-site work, and can articulate clear trade-offs in their system designs.