Top Artificial Intelligence Jobs in Pittsburgh, PA

Design, build, and own reliable, secure, and performant production systems for clinical workflows. Make high-stakes technical decisions, improve code and designs via reviews, collaborate with product/design/clinical experts, debug and harden complex systems, and help shape technical and architectural direction at senior levels.

Sell Candid Health's revenue cycle management solutions to ambulatory practices and health systems nationwide. Qualify and close complex multi-stakeholder enterprise deals (high six- to seven-figure), build C-level relationships, lead coordinated deal strategy with Solutions Consultants, and provide field insights to inform product, delivery, and go-to-market strategy while exceeding pipeline and revenue targets.

Lead and grow the backend engineering team that owns the high-traffic application process. Own technical direction, architecture, delivery, hiring, and hands-on engineering (design/code reviews). Partner with product and design to take ambiguous problems to production while raising engineering standards.

Own onboarding, administration, configuration, and internal operational workflows for ServiceTitan Communications products. Define roadmaps, write PRDs and user stories, build AI-assisted prototypes, partner with cross-functional teams, and measure outcomes to reduce operational friction and improve adoption and reliability.

Lead and scale a global SRE team to ensure 4-9's availability, run 24x7 operations and incident command, own release management, capacity planning, performance tuning, and observability. Drive SRE practices, CI/CD, IaC, containerization, pre-production performance/DR constructs, and partner with engineering leadership to improve reliability, uptime, and operational processes.

Lead the design and implementation of end-to-end quality systems and testing frameworks. Own multiple testing layers (unit, integration, E2E, contract, performance, chaos), integrate automated tests into CI/CD, drive load/performance testing and monitoring, troubleshoot failures, apply AI tooling to improve workflows, and collaborate with engineers, PMs, and designers to improve coverage and reliability.

Lead global web strategy and organic discoverability for Harness.com, owning SEO/AEO for search and AI answer engines, site architecture, conversion optimization, measurement, and vendor management. Partner with product marketing, content, demand gen, and developers to drive traffic, AI-driven visibility, and conversions through technical SEO, content strategy, experiments, and performance standards.

As an Enterprise Sales Development Representative, you'll focus on generating outbound leads in the commercial construction market, engaging prospects through cold calls while understanding their needs. You'll develop effective outreach strategies and improve sales insights.

Outbound-focused Sales Development Representative responsible for generating pipeline through multi-channel prospecting (phone, email, LinkedIn, short-form video), scheduling high-quality meetings, researching accounts, maintaining CRM data, collaborating with AEs/Marketing/Product, iterating messaging, and hitting monthly KPIs.

Lead full-cycle technical recruiting for systems, database, distributed-systems, and ML/AI roles. Source, screen, and close candidates; build talent maps and outreach; design engineering-specific interview loops and scorecards; partner with hiring managers; operate ATS and AI sourcing tools; represent LanceDB to technical communities.

Own technical qualification of compute providers: define acceptance standards and benchmarks, validate clusters (fabric, GPUs, storage, orchestration), guide provider remediation, and maintain technical relationships to ensure reliable production performance.

Embed with customer teams running large-scale GPU training and inference to onboard, tune, debug, and improve reliability. Diagnose fabric, driver, scheduler, and application failures; profile performance; build automation, monitoring, and preflight checks; lead incident response; and convert field learnings into product improvements and reusable reference configurations.

Lead end-to-end engineering for production AI agents and platform systems. Own architecture, deployment, scalability, security, and reliability. Use agentic coding to accelerate development, mentor teammates, and collaborate with data scientists and customers to deliver production-grade AI workflows.