Top Tech Jobs & Startup Jobs in Houston, TX

Manage a portfolio of B2B SaaS accounts throughout the customer lifecycle, building executive relationships, conducting business reviews, monitoring health and churn risk, and supporting renewals. Identify expansion opportunities with Account Executives, synthesize customer feedback for Product and Engineering, and advocate for customer needs. The role requires strong communication, analytical ability, attention to detail, resourcefulness, and cross-functional collaboration. Remote work is available across US time zones.

Lead the vision, strategy, and execution of Oyster’s Employer of Record product across onboarding, payroll, benefits, compliance, and offboarding. Manage and develop a multi-layered product organization, prioritize complex initiatives, and partner with Engineering, Design, Legal, Finance, and Operations. Drive AI-powered automation, scalable workflows, measurable business outcomes, and product quality across a regulated global employment platform.

Own and scale product marketing, content, and sales enablement end-to-end: GTM messaging, launches, sales materials, competitive differentiation, and measurement to drive pipeline, deal acceleration, and win rates. Manage multiple senior initiatives, align cross-functional stakeholders, and use AI to scale output and optimize results.

Leads a controls support engineering team responsible for post-commissioned warehouse automation systems. Oversees technical issue resolution, escalations, resource allocation, documentation, system reliability, and customer satisfaction. Develops measurable cross-training programs across multiple controls platforms, tracks capability progress through KPIs and skills matrices, and mentors team members. Collaborates with software, mechanical, and site operations teams to improve system performance and support processes.

Leads vCISO and cybersecurity compliance engagements for multiple clients, including CMMC and NIST assessments, SSP and POA&M development, risk assessments, framework mapping, audit and assessor support, incident response, and remediation coordination. Advises clients on regulatory obligations, security tooling, and compliance strategies while managing client relationships, engagement health, reporting, and delivery quality across a large portfolio.

Design, deploy, and manage machine learning models supporting client acquisition, retention, and reactivation. Develop Next Best Action, CRM, paid media, and personalization solutions using LLMs and traditional ML. Design and interpret experiments, analyze large-scale datasets, communicate recommendations to stakeholders, and collaborate with product, design, and engineering teams on product and infrastructure roadmaps.

Advises legal customers on adopting and integrating Relativity’s AI platform. Builds relationships with lawyers, leads tailored demonstrations, supports pre-sales, onboarding, training, workflow transformation, and value realization. Translates AI capabilities into practical legal use cases, gathers customer feedback for product teams, and develops scalable engagement best practices. The role requires a practicing or former attorney with litigation knowledge, strong communication skills, and hands-on experience with legal AI tools.

Design and deliver enterprise-grade Generative AI solutions on AWS using Bedrock and AgentCore. Architect LLM-based applications, RAG pipelines, agentic workflows, vector DB integrations, and APIs. Optimize models for performance, cost, and quality, ensure security and governance, lead teams, and troubleshoot production GenAI systems.

Leads enterprise LifePRO, TPA, digital platform, and AI-enabled transformation programs from planning through deployment, stabilization, and adoption. Oversees architecture, engineering, integrations, data migration, testing, release, and production governance while aligning diverse applications to a unified strategy. Engages executive clients, manages risks and escalations, builds global delivery teams, and drives AI adoption, modernization, operational excellence, and permanent defect reduction across complex insurance ecosystems.

Lead experimentation and decision science initiatives from problem definition through recommendations. Design and analyze A/B tests, quasi-experiments, matched-market tests, and causal inference studies. Apply advanced statistics, regression, predictive modeling, machine learning, and big-data analysis using Python, R, SQL, and PySpark. Partner with stakeholders, communicate actionable findings, build reproducible workflows, and mentor analysts and junior data scientists.