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

Designs and maintains Retrieval-Augmented Generation systems, including document ingestion, indexing, semantic and vector search, embeddings, and enterprise knowledge repositories. Integrates retrieval services with LLMs through APIs and scalable cloud-native architectures. Monitors accuracy, performance, security, governance, and data quality while troubleshooting systems and evaluating emerging retrieval technologies. Collaborates with AI engineers and product teams to deliver reliable, context-aware AI solutions.

The Executive Recruiter manages the full recruitment lifecycle for executive and leadership roles, including sourcing, talent mapping, candidate evaluation, interviews, and placement. The role partners with senior leaders and hiring managers, maintains executive talent pipelines, provides market and compensation insights, monitors recruitment metrics, and delivers a positive candidate experience across multiple regions.

Evaluates and validates AI chatbot functionality, response quality, conversational flows, compliance, and user experience. Executes test plans, regression testing, and user acceptance testing; documents defects and test outcomes; analyzes interaction trends; collaborates with AI trainers, prompt engineers, and development teams; prepares performance reports; and supports chatbot optimization and evaluation framework improvements.

Leads organization-wide prompt engineering strategy, standards, governance, and optimization. Designs advanced prompts and reusable libraries for enterprise AI applications, establishes evaluation benchmarks and quality processes, analyzes model outputs, and drives performance improvements. Partners with executives, product managers, engineers, and business stakeholders to translate requirements into AI solutions. Mentors prompt engineers, evaluates emerging AI platforms, and supports innovation and enterprise AI transformation initiatives.

Leads AI data annotation operations, managing workflows, resources, production targets, quality standards, audits, and performance metrics. Oversees annotation teams through coaching, recruitment support, onboarding, and performance management. Partners with AI engineers, trainers, product teams, and operational stakeholders to translate requirements into plans. Drives process improvement, automation, tool adoption, data integrity, and operational excellence across AI and machine learning data preparation initiatives.

Leads the global sales organization by developing sales strategy, expanding markets, driving revenue, managing strategic partnerships, and overseeing sales operations. Builds and mentors geographically dispersed teams, manages enterprise sales cycles, monitors performance metrics, oversees budgets, collaborates cross-functionally, and represents the company at industry events. Extensive travel is required.

Leads the architecture, development, deployment, governance, and optimization of enterprise Generative AI solutions. Builds applications using LLMs and foundation models, develops prompt engineering frameworks, supports AI strategy, ensures secure and responsible deployment, mentors engineers, evaluates emerging technologies, and translates business needs into scalable technical architectures.

Leads end-to-end M&A integration from pre-acquisition planning through Day 1 readiness and post-close transformation. Responsibilities include negotiating Transaction Service Agreements, developing integration roadmaps, coordinating cross-functional workstreams, tracking synergies and ROI, managing risks, supporting executive governance, and implementing change management. The role also builds integration capabilities, coaches stakeholders, and ensures operational continuity across HR, Finance, IT, Operations, and other functions.

Leads the strategy, roadmap, development, launch, and optimization of AI-powered products. Defines product vision, requirements, priorities, success metrics, and adoption goals while coordinating engineering, AI, business, executive, and customer stakeholders. Evaluates emerging AI capabilities, supports responsible AI governance, manages product performance, and drives continuous improvement aligned with business objectives.

Leads the design, development, and optimization of enterprise Retrieval-Augmented Generation platforms. Responsibilities include building retrieval architectures, ingestion and indexing frameworks, vector search, semantic retrieval, LLM integrations, scalable APIs, evaluation frameworks, governance controls, monitoring, troubleshooting, and performance optimization. The role provides technical leadership, mentors engineers, evaluates emerging technologies, and supports enterprise AI strategy and deployments.