Top Artificial Intelligence Jobs in Pittsburgh, PA

Develop, test, maintain, and support enterprise applications and services using C#, .NET, ASP.NET Core, Web API, Entity Framework Core, and SQL Server. Responsibilities include API and database integration, code reviews, automated testing, debugging, performance improvements, release readiness, production troubleshooting, and collaboration with product, architecture, QA, and operations teams.

Own the end-to-end network architecture for GPU data center fabrics, backbone and edge delivery, cloud and hybrid connectivity, operations, automation, capacity planning, and vendor relationships. Design high-performance Ethernet and InfiniBand networks, optimize latency and resilience, establish observability and incident practices, and lead through technical authority. The role also sets standards, mentors engineers, shapes hiring, and uses AI tooling to accelerate network design, automation, analysis, and documentation.

Unpaid remote internship focused on data extraction, scraping, mining, processing, cleaning, pipeline development, AI model training, and containerized microservices. The intern will use Django, Puppeteer, Selenium, Docker, Pandas, NumPy, Scikit-learn, Git, and GitHub while applying testing and data engineering practices. The role requires at least 30 hours weekly and may convert to full-time employment.

Build AI-enabled features for a legal technology platform, proactively improve products, and drive engineering projects from concept through completion. The role offers growth into independent contributor or engineering management responsibilities. The company focuses on using AI to support commercial contract negotiation and expand legal technology applications.

Build and scale AI agents for sales enablement across frontend and backend systems. Lead development with Next.js, React, TypeScript, Python, Postgres, OpenAI, and FastAPI; design robust AI integrations, engage customers, contribute to roadmap planning, and iterate rapidly in a high-ownership startup environment.

Manage and grow strategic enterprise accounts through consultative upselling, cross-selling, renewals, and complex expansion sales. Build executive relationships, lead multi-stakeholder sales cycles, conduct presentations and demonstrations, maintain CRM pipeline forecasts, and meet revenue targets. Collaborate with client engagement, product, marketing, and revenue operations teams while identifying account risks and opportunities. Mentor junior team members and improve sales processes.

Drive enterprise SaaS sales from prospecting through close, expanding adoption among strategic accounts. Engage business and technical decision-makers, including C-suite stakeholders, to address fraud challenges using Sift’s machine learning platform. Build consultative business cases, articulate platform differentiation, collaborate cross-functionally, and help shape sales strategy and growth. Requires strong organizational skills, adaptability, and experience managing complex B2B sales cycles.

Build and scale backend infrastructure for AI-driven freight finance workflows, including document processing, APIs, data pipelines, audit engines, integrations, observability, and performance monitoring. Collaborate with AI/ML teams to productionize model outputs, integrate freight and financial systems, improve engineering practices, and make frontend updates as needed in a remote-first startup environment.

Lead onboarding and implementation for agency and SMB clients. Configure and troubleshoot CRM and platform integrations, APIs, webhooks, and AI phone workflows in live environments. Collaborate with engineering, product, and customer success teams to resolve technical issues, improve product adoption, document repeatable workflows, and train clients. The role requires strong technical communication, SaaS implementation experience, and comfort working autonomously in a fast-paced startup.

Onboard new customers, support product deployment, and create playbooks for customer success and new-hire training. The role works closely with the CEO and CSO at a climate technology startup, addressing ambiguous problems and developing innovative solutions for agriculture and energy customers. Experience in customer success or product management is required; agriculture, SaaS, and early-stage startup experience are preferred.