Top Tech Jobs & Startup Jobs

Design, develop, deploy, and operate production-grade AI applications, agents, backend services, and AI infrastructure. Build MCP integrations, RAG and multi-agent workflows, inference pipelines, APIs, asynchronous services, evaluation systems, and observability capabilities. Own deployments, CI/CD, security, monitoring, reliability, and production support using cloud infrastructure, Docker, and Kubernetes. Transition AI prototypes into secure, scalable, observable systems while improving quality, latency, reliability, and operational cost.

Own paid customer acquisition across digital advertising channels, managing campaigns, budgets, experimentation, analytics, tracking, and funnel optimization. The role requires hands-on optimization across Google Ads and additional platforms, structured A/B testing, creative performance analysis, landing page improvements, and accurate reporting through Google Analytics 4 and Google Tag Manager. The lead will collaborate with Creative, Product, Engineering, Analytics, Sales, and leadership teams to improve CAC, ROAS, conversion rates, and revenue.

Prepare and review individual U.S. income tax returns, identify complex tax edge cases, validate product outputs against professional tax software, and collaborate with engineers and founders to improve tax product functionality, roadmap, and user experience. The role requires substantial tax-season experience, strong federal tax knowledge, and expertise with professional tax preparation platforms.

Prepare and review individual U.S. income tax returns, identify complex tax scenarios and product edge cases, validate tax engine outputs against professional tax software, and collaborate with engineers on tax rules, product improvements, and user experience. Serve as a tax subject matter expert embedded within an early-stage product and engineering team.

Reviews and evaluates domain-specific documents, providing structured feedback on quality, accuracy, and relevance. The role requires strong analytical and written communication skills, detailed document review, proficiency with spreadsheet and presentation software, and the ability to follow structured guidelines. Candidates must have a bachelor’s degree, at least three years of relevant professional experience, English proficiency, and reside in the United States, Europe, the United Kingdom, or Canada.

Builds a talent network of experienced data scientists for potential future AI evaluation projects. Responsibilities may include creating grading criteria, evaluating AI-generated or human-produced data science work, writing evidence-based justifications, applying consistent judgment, and incorporating reviewer feedback. Candidates should have professional data science experience, strong Python and SQL skills, expertise in statistical modeling, machine learning, experimentation, causal inference, and excellent technical communication.

Develop and evaluate realistic Excel tasks and solutions for AI training data. Apply advanced Excel capabilities including formulas, PivotTables, data modeling, dashboards, Power Query, Power Pivot, and VBA across multiple industries and business functions. Provide written feedback, close research knowledge gaps, improve model performance, and collaborate with subject matter experts. Requires reliable weekday availability, initially 40 hours per week and 20 hours thereafter.

Reviews accounting and audit tasks and AI model outputs, identifies technical errors, writes instruction specifications and golden solutions, designs domain benchmarks, and translates professional judgment into evaluation criteria. Requires an active accounting or audit credential, substantial accounting or audit experience, specialization in a relevant domain, senior-level progression, hands-on large language model experience, strong written communication, and 40-hour weekly availability for six months in a hybrid Bay Area role.

Design and manage compensation and equity programs, including salary bands, leveling frameworks, annual compensation cycles, incentive structures, option and RSU programs, 409A valuations, grant administration, equity modeling, and employee communications. Valuable experience includes pay equity, pay transparency, global or contractor compensation, benefits design, HRIS and compensation tooling, executive compensation, plan governance, and IPO readiness.

Reviews engineering tasks and AI model outputs, creates instruction specifications and golden solutions, designs engineering benchmarks, and translates expert judgment into evaluation criteria. Requires hands-on production software or systems engineering experience, specialization in a technical domain, senior-level ownership, AI fluency, strong written communication, and full-time availability for a six-month hybrid Bay Area engagement.