Top Artificial Intelligence Jobs in Pittsburgh, PA

Test new web and mobile features, report bugs and usability issues, run manual and automated tests, review requirements and designs, improve QA processes and documentation, and provide UI/UX feedback while collaborating with product, design, and engineering teams.

Acquire and grow mid-market customers for AI-powered customer experience, contact center, unified communications, and business communication solutions. Generate pipeline through prospecting, referrals, networking, partners, and inbound opportunities; manage complex multi-stakeholder sales cycles; conduct consultative discovery; develop account plans; present solutions; maintain CRM data and forecasts; use AI-enabled sales tools and analytics; and collaborate with marketing, partners, solution consultants, customer success, and product teams.

Build and iterate full-stack systems powering AI agents, from user-facing experiences through orchestration and deployment. Research agent orchestration, prompting, and model alignment approaches; collaborate with Product, Design, and Engineering to improve usability; document findings, share technical learnings, and participate in reviews and technical discussions.

Make phone calls to nonprofit executive directors using a provided parallel dialer and script, qualify prospects, schedule 30-minute consultations, and record activity in the CRM. The role is fully remote, 40 hours weekly during US business hours, with a 20-hour paid trial week. Compensation includes a $20 hourly base, attended-consult bonuses, and signed-client bonuses.

The Senior Data Scientist will analyze large-scale customer data, investigate behavioral questions, design and automate studies, and translate findings into actionable recommendations. The role includes maintaining analytics frameworks, documenting methodologies, writing white papers, and communicating insights across the company. Candidates should be independent, comfortable with ambiguity, and experienced with SQL and Redshift. Python or R, machine learning, Spark, A/B testing, and cross-functional experience are preferred.

Own a portfolio of strategic enterprise customers from implementation through renewal. Build success plans, manage adoption and value realization, engage executives, forecast renewals, mitigate churn risk, and identify expansion opportunities with Account Management. Lead business reviews, roadmap discussions, customer escalations, and cross-functional coordination. Translate customer feedback into product priorities and advise executives on agentic AI, generative AI, and enterprise CX opportunities and risks.

Drive revenue growth by developing strategic publisher partnerships, expanding the publisher network, prospecting and closing enterprise accounts, managing complex sales cycles, exceeding targets, forecasting pipeline performance, and maintaining long-term stakeholder relationships. The role requires close collaboration with internal teams and strong communication in a fast-paced startup environment.

Build and maintain 3D pipeline integrations, plugins, exporters, and platform connections across DCC tools and SaaS destinations. Own integrations from scoping through deployment, documentation, release, and support. Ensure asset fidelity across formats, materials, textures, scene scaling, and color spaces while troubleshooting complex multi-system pipelines. Collaborate with internal engineering teams, external platform vendors, and customers to resolve integration constraints and extend the shared integration framework.

Embed with client teams to design, build, and ship production-grade AI systems (LLM-powered apps, RAG, agents). Own architecture, write maintainable tested code, debug production issues, transfer knowledge, and contribute learnings, docs, and internal tooling.

Lead go-to-market strategy and launches for an agentic AI business unit serving regulated life sciences buyers. Develop product positioning, messaging, narratives, sales enablement, campaigns, and customer-facing value propositions. Partner with Product, Sales, Demand Generation, and Revenue Operations, track pipeline and revenue impact, and use AI tools to streamline marketing execution. The role requires B2B SaaS or technology marketing experience, strong technical writing, product launch expertise, and cross-time-zone collaboration.