Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Manage complex web marketing programs from intake through launch, coordinating marketing, product, design, engineering, analytics, SEO, legal, and brand stakeholders. Responsibilities include prioritizing initiatives, managing timelines and dependencies, mitigating risks, improving web performance and user experience, establishing governance processes, and using analytics to guide recommendations and roadmap decisions.

Designs, deploys, and integrates generative AI solutions for clients, including LLM agents, RAG pipelines, workflow automation, and conversational interfaces. Translates business needs into production systems, supports adoption through training and iteration, contributes to AI research and offerings, and assists with business development and publications.

The consultant identifies and prioritizes enterprise AI opportunities, translates business challenges into AI use cases, designs and prototypes AI-powered workflows, and supports scaled implementation. Responsibilities include coordinating cross-functional delivery, establishing governance and operating models, measuring adoption and business impact, optimizing prompts and workflows, and enabling organizational change through training and stakeholder engagement. The role requires strong consulting, generative AI, communication, and solution-oriented skills.

Manage high-volume in-app editorial and marketing content delivery across multiple app surfaces. Own intake, tracking systems, calendars, asset trafficking, QA, approvals, launch coordination, risk escalation, and cross-functional status cadences. Partner with creative, brand, product marketing, product, engineering, and agency teams to deliver concurrent work on schedule. Improve workflows through templates, automation, and generative AI while maintaining human quality review.

Designs, develops, fine-tunes, evaluates, and deploys generative AI and LLM solutions for clients. Responsibilities include prompt engineering, RAG architecture, model selection, application development, MLOps integration, cloud deployment, evaluation, security, compliance, and responsible AI. The consultant collaborates with technical and nontechnical stakeholders, researches emerging AI methods, documents practices, and helps distinguish GenAI use cases from traditional NLP applications.

Leads brand direct-response creative production, including briefing, creative development, quality review, feedback, testing, and optimization. Partners with brand, product marketing, creative, and external agency stakeholders to deliver high-quality, brand-consistent assets on tight timelines. Requires strong experience in brand marketing, creative production, direct response, stakeholder management, and management consulting.

Lead end-to-end architectures for cloud, data, machine learning, deep learning, generative AI, and agent-based systems. Serve as the technical authority for client engagements, aligning solutions with business, security, compliance, scalability, reliability, and cost requirements. Lead architecture reviews, guide engineering teams, oversee delivery from assessment through production, and support pre-sales proposals and estimations. Mentor consultants and engineers while developing internal AI accelerators and reference architectures.

Designs and deploys production generative AI solutions, including LLM agents, RAG pipelines, workflow automation, and conversational interfaces. Integrates solutions with client APIs, databases, cloud environments, and business tools. Leads adoption through training, evangelization, stakeholder collaboration, and continuous iteration. Contributes to AI research, internal offerings, publications, and business development while bridging technical teams and business decision-makers.

Leads client engagements focused on risk and compliance process design, operational transformation, AI opportunity identification, workflow automation, and business analysis. Maps processes, identifies risks and inefficiencies, develops improved frameworks and AI-enabled solutions, manages project workstreams, presents recommendations to stakeholders, mentors team members, supports proposals, and contributes to thought leadership around AI in regulated environments.

Support client compliance and risk teams by defining data needs, building data pipelines, analyzing structured and unstructured data, and deploying ML/GenAI solutions (LLMs, agents). Design, fine-tune, and productionize LLM-based systems, implement monitoring and dashboards, ensure regulatory compliance (GDPR, EU AI Act), and collaborate with engineering and product teams while contributing to internal training, publications, and business development.