Top Artificial Intelligence Jobs in Pittsburgh, PA

Write and adapt technical and non-technical content across social media, blogs, founder communications, and company announcements. Translate research papers and technical findings into accessible writing, maintain distinct brand and founder voices, verify claims, collaborate with stakeholders, repurpose content across channels, and independently manage deadlines for a part-time contract.

Senior Product Designer shaping AI agent platforms for developers and enterprise users. Responsibilities include defining product direction, designing and prototyping coded experiences across command-line, web, console, collaboration, onboarding, and documentation surfaces, developing design systems, conducting user research and usability testing, analyzing product analytics, creating data visualizations, and collaborating with Product, Engineering, design, and go-to-market teams.

Supports client-facing technical issues, escalates bugs, monitors production systems, troubleshoots web and email problems, updates backend data, and contributes to software features, data pipelines, APIs, and responsive applications. Works cross-functionally with Engineering, Product, QA, and Data teams while developing skills in web technologies, SQL, cloud environments, accessibility, and generative AI.

Own and expand a portfolio of 6–9 strategic health system accounts, lead complex enterprise sales and multi-year expansions, and selectively pursue marquee national accounts. Build executive relationships across clinical, operational, financial, and IT stakeholders; develop CFO-grade ROI models; shape decision criteria; negotiate high-value agreements; and coordinate cross-functional teams to drive adoption, value realization, forecasting, and long-term account growth.

Deploy and support distributed SaaS and on-premise infrastructure, gather customer requirements, adapt deployment manifests, monitor platform health, troubleshoot issues, package releases, and automate release pipelines across Kubernetes and AWS, GCP, and Azure environments.

Build and maintain Django-based web applications, design RESTful APIs, implement frontend features (HTML/CSS/JS), optimize performance and security, collaborate with cross-functional teams throughout the development lifecycle.

Leads a span of approximately 20 engineers while shaping hiring, onboarding, career development, staffing, and engineering enablement across the AI practice. The role is also approximately 50% billable client delivery, providing executive advisory on AI software development lifecycles, governance, agentic deployments, MLOps and LLMOps pipelines, cloud platforms, observability, and production resilience. Requires extensive engineering leadership, organizational scaling, consulting, GCP, and production AI/ML deployment experience.

Build and operate scalable cloud data pipelines, warehouses, transformation layers, and ML production systems. Lead data infrastructure architecture, warehouse performance optimization, DataOps monitoring, CI/CD improvements, data quality testing, and large-scale data product delivery. Collaborate across teams, promote data stewardship, and support batch and streaming pipelines while deploying, serving, and monitoring machine learning models.

The Product Analyst connects product vision with software development by translating customer needs into user stories, acceptance criteria, and prioritized backlogs. They support Agile sprint planning, product roadmap development, stakeholder communication, release planning, and customer workflow research. The role gathers feedback, evaluates competitors, identifies risks and opportunities, and ensures development teams understand business goals and expected outcomes.

Manage inbound leads from marketing channels, communicate Automation Anywhere’s value proposition, qualify prospects, schedule discovery calls for Account Executives, maintain lead records in Salesforce and Salesloft, and contribute to revenue pipeline goals through phone, email, and social outreach.