Software development company for San Francisco teams

Ryz Labs provides senior software engineers and AI pod teams for San Francisco companies, working remotely from Latin America on Pacific time business hours. Trusted by Fortune 500 engineering teams, our engineers are the top 1% of the tens of thousands we interview, and they work in your repos, your cloud and your on-call rotation. We don't have a San Francisco office; we are the nearshore option for Bay Area teams that need senior people shipping on their own clock.

What we build for San Francisco teams

San Francisco's software economy is dominated by venture-backed SaaS, AI startups, fintech and developer tooling, alongside the enterprise engineering groups based around the Bay. The work our teams take on reflects that mix.

• B2B SaaS platforms: multi-tenant architecture, SSO and SCIM provisioning, usage-based billing, audit logs and the admin surfaces enterprise buyers ask for in security reviews. See SaaS.
• LLM features in production: retrieval pipelines, agents with tool calling, evaluation suites and cost and latency controls on top of OpenAI and Anthropic models. See LLM development.
• Fintech products: ledgers, card and ACH flows, Plaid and Stripe integrations, KYC onboarding and reconciliation jobs. See fintech.
• Developer tools and APIs: public APIs with versioning and SDKs, CLIs, webhooks, and the docs and rate limits that make them usable.
• Data platforms: event pipelines into Snowflake, BigQuery or Databricks, dbt models and the product analytics growth teams depend on.
• MVPs after a raise: a funded team that needs a working product in front of design partners, built so it survives the next round of hiring. See MVP development.

Pacific hours, from Latin America

Latin America is one to five hours ahead of San Francisco depending on the country and the time of year. Engineers in Mexico City or Costa Rica start close to your morning; engineers in Bogotá are two or three hours ahead; engineers in Buenos Aires or São Paulo work a later day to cover yours. We match on working hours during scoping, so the team is online for your standup, your afternoon review queue and your deploy window.

That matters most for teams already running a split between the Bay and an offshore office eight to twelve hours away. Every question to that office becomes a next-day answer. A team on Pacific hours closes the loop the same afternoon, and an incident page reaches the people who wrote the code.

The stack our teams work in

Most Bay Area codebases we see are TypeScript end to end (React, Next.js and Node.js) or a Python or Go back end, on Postgres, deployed to AWS or GCP with Terraform and GitHub Actions. AI work adds OpenAI and Anthropic models, vector search in pgvector or a dedicated store, and orchestration code your team can read without a framework tutorial. Our engineers adopt your conventions, linters and review rules rather than importing their own, so the code still looks like yours a year later.

How an engagement works

1. Talk. A scoping call on Pacific time: the system, your stack, your roadmap pressure and what your current team should keep owning.
2. Match. We propose a team with names, seniority, working hours and a monthly price. You meet the engineers before anything starts.
3. Join. The team gets access to GitHub, CI, your cloud accounts and Slack, attends your rituals and opens its first pull requests.
4. Grow. Add engineers, an ML engineer or a designer as the roadmap changes, or hand the system to your in-house team.

What goes wrong in startup and AI codebases

Bay Area codebases tend to fail in predictable ways after fast growth. Senior engineers spot these early.

• LLM features without evals. A prompt change that looks better in a demo can quietly break edge cases. Our teams build evaluation sets from real traffic, run them in CI and track cost and latency per request before scaling a feature.
• Tenant isolation added late. Shared tables without tenant scoping are a security-review blocker. Teams add row-level security or scoped repositories with tests that prove one customer can't read another's data.
• Billing that doesn't match usage. Usage-based pricing breaks when metering events are dropped or double-counted. Idempotent event ingestion and daily reconciliation against the billing provider fix it.
• Compliance reviews that stall deals. Enterprise buyers ask for SOC 2 reports and evidence of access controls. Our engineers have experience working within SOC 2 controls; your compliance owner and auditor own the attestation.
• Prototype code in production. The MVP that won the round now carries real customers. Teams add tests around the money and permissions paths first, then refactor behind feature flags.

AI pod teams for Bay Area companies

If the goal is a production AI system rather than more hands on the backlog, an AI pod team is the better shape: a dedicated pod of senior engineers, for example a tech lead, an ML engineer and back-end engineers, building in your cloud and repos alongside your team. Our pods have shipped an AI voice platform, an AI driver-support agent and fraud detection for a global fleet company; see case studies.

Team shapes and cost

Typical Ryz cost is $7,000–$15,000 per engineer per month, mostly mid-level to senior: mid-level (comparable to Amazon L5) $7,000–$10,000, senior (comparable to Amazon L6) $10,000–$15,000, and leads $15,000+, quoted per team.

• Two seniors on your team: 2 × $10,000–$15,000 = $20,000–$30,000 per month, working from your backlog.
• AI pod: a tech lead plus 6 senior engineers across ML, back end and data. 6 × $10,000–$15,000 = $60,000–$90,000, plus the lead at $15,000+, so about $75,000–$105,000+ per month.
• Four-month MVP: team size × duration × monthly rate. Three engineers for four months at $7,000–$15,000 is 3 × 4 × $7,000–$15,000 = $84,000–$180,000.

You get a scoped plan, a price and the names of the people who would do the work before you start.

When Ryz isn't the right fit

If your company requires everyone in the office in SoMa or Palo Alto every day, hire locally. If you are hiring a founding engineer for the long haul, a direct hire through our placement services fits better than a team. If you want a self-serve freelance marketplace, hourly gigs or a proprietary AI platform you license, other providers fit better.

Related

• Software development companies in San Francisco
• Software development for Seattle teams
• Staff augmentation
• Forward-deployed engineers

FAQ

Do you have an office in San Francisco?

No. Our engineers work remotely from Latin America on Pacific time business hours, with real-time overlap for standups, code review and incidents.

How much does a software team for a San Francisco startup cost?

Typical cost is $7,000–$15,000 per engineer per month, mostly mid-level to senior, with leads at $15,000+ quoted per team. A pair of senior engineers is $20,000–$30,000 per month. You get a plan, a price and names before you start.

Can your engineers build LLM and agent features?

Yes. Our AI pod teams build retrieval, agents and evaluation pipelines on OpenAI and Anthropic models, in your cloud on AWS or Azure, and ship them to production with your team.

Will a Latin American team slow down a fast-moving startup?

The opposite is the goal. Senior engineers on Pacific hours review code the same day, take on-call shifts and ship from your backlog from the first weeks. Pace still depends on scope and how quickly you grant access.

Do you only work with startups?

No. We serve enterprises across industries as well as venture-backed companies. SaaS, AI and fintech are listed because they are common in San Francisco.

Questions we didn't answer? Email info@ryzlabs.com.