Top Artificial Intelligence Jobs in Pittsburgh, PA

Manage cross-functional event projects from planning through execution, including timelines, budgets, dependencies, vendors, venues, promotional materials, and on-site logistics. Identify risks, resolve blockers, communicate status and run-of-shows, and improve event workflows. The role supports field marketing events, trade shows, sponsorships, virtual experiences, and multiple simultaneous initiatives while coordinating Marketing, Sales, and external partners.

Leads enterprise data security and information governance by building data intake, catalog, marketplace, classification, lineage, and access-control programs. Translates privacy and security requirements into technical controls, self-service workflows, and governance documentation. Partners with Legal, InfoSec, engineering, product, and data teams to support compliant data use, AI/ML initiatives, and regulatory requirements including HIPAA, GDPR, and CCPA. Measures adoption, turnaround times, and governance maturity across a global SaaS organization.

Serve as a strategic finance partner to Product leadership, building financial models, forecasts, business cases, and scenario analyses for growth initiatives, pricing, investments, and resource allocation. Analyze SaaS metrics such as ARR, retention, churn, and unit economics, translating complex data into recommendations for senior leaders. Collaborate across Product, Finance, Data Science, and Marketing while improving analysis through automation, standardized processes, and AI-enabled workflows.

Lead and grow an enterprise sales team selling AI-powered SaaS underwriting and analytics solutions to health insurance and benefits organizations. Responsibilities include recruiting, coaching, forecasting, quota attainment, pipeline management, strategic deal support, onboarding, performance improvement, and leadership reporting. The role partners with Marketing, Product, and Customer Success to shape demand generation and messaging while driving consultative sales methodology across the team.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Develop and maintain production machine learning models, build scalable training and serving technologies, optimize real-time and batch ML pipelines, and monitor model performance and drift. The role involves deep neural networks, recommendation systems, automated retraining, ML research, engineering excellence, and communicating technical concepts to diverse audiences. Candidates need 6+ years of industry ML experience, strong coding skills, and experience deploying neural networks at scale.

Lead the Performance and Quality Frameworks team, owning scalable performance engineering platforms and shared functional testing frameworks. Drive architecture, reliability, adoption, documentation, self-service, and roadmap execution across product teams. Apply AI tools such as Cursor and Claude Code to improve test development, maintenance, analysis, and engineering efficiency. Partner with cross-functional stakeholders, mentor engineers, measure framework outcomes, and support highly distributed SaaS systems using cloud, microservices, containers, and CI/CD technologies.

Leads the strategy, architecture, implementation, and evolution of enterprise analytics platforms. Responsibilities include designing scalable data platforms, integrating digital and enterprise data, establishing governance and security standards, optimizing analytics and BI capabilities, evaluating cloud technologies, managing platform performance and risks, and mentoring technical teams. The role also requires close collaboration with executives, clients, Product, Engineering, Data Science, Marketing, and business stakeholders.

Own and mature the company’s DevSecOps and cloud security function. Responsibilities include implementing SOC 2 controls, automating compliance evidence, managing cloud security posture and runtime security, embedding security gates into CI/CD, leading vulnerability remediation, developing auto-remediation and AI-assisted workflows, and securing infrastructure through Terraform and policy-as-code. The role also partners with GRC and corporate security teams while building reusable security tooling and developer-platform guardrails.

Serve as the primary technical contact for enterprise customers, translating business needs into technical requirements and scalable solutions. Develop architecture strategies, documentation, and best-practice guidance; conduct proofs of concept, product demonstrations, training, and workshops. Troubleshoot complex infrastructure issues, advise on observability and enterprise technology, and collaborate with sales, product, and customer experience teams. Gather customer feedback to influence the product roadmap and support successful adoption of the LogicMonitor platform.