Top Artificial Intelligence Jobs in Pittsburgh, PA

The Solutions Engineer partners with Sales, Customer Success, Product, Engineering, and Support to guide customers from discovery through implementation and expansion. Responsibilities include technical discovery, solution and workflow design, onboarding, QA, deployment, RFP and RFI responses, customized product demonstrations, and advising clients across web, iOS, Android, and cloud integrations. The role also advocates for customer needs and drives product improvement.

Design, develop, and maintain scalable backend services and APIs (Node.js, Firebase). Optimize performance, ensure code quality via reviews and unit tests, debug and upgrade systems, and contribute to frontend work as needed. Stay current on backend and Gen AI integrations and collaborate across the team.

Own product direction, roadmap, priorities, and outcomes for an AI platform serving contractors. Lead customer discovery, product strategy, requirements, launches, measurement, and iteration while partnering closely with leadership, engineering, and customer-facing teams. Make evidence-based product decisions, prototype with AI tools, manage technical tradeoffs, and establish scalable product management practices in an early-stage company.

Design and lead scalable data engineering solutions across Databricks and Microsoft Azure. Define enterprise data modeling standards, architect pipelines and integrations, establish engineering best practices, troubleshoot complex platform issues, and guide modernization and cloud migration initiatives. Provide technical leadership and mentorship while ensuring data platforms meet security, quality, governance, reliability, performance, and maintainability standards.

Own the product strategy, roadmap, and ongoing operations for KarmaCheck’s ATS, HRIS, HCM, VMS, partner, and public API integrations. Define data flows, API and webhook capabilities, versioning, error handling, documentation, and implementation tooling. Partner with engineering and external platforms, support customer discovery and enterprise sales, scope implementations, enable internal teams, and bring AI and screening products into customers’ existing systems.

Owns the end-to-end deployment of unmanned forklifts, from project kickoff and planning through on-site setup, commissioning, validation, and completion reporting. Acts as the technical liaison among customers, engineering teams, SI partners, manufacturers, and ODM vendors. Responsibilities include requirements analysis, project scheduling, system integration support, troubleshooting, stakeholder communication, deployment documentation, and field feedback. Requires extended travel and assignments in warehouses or industrial environments.

Build and operate security-critical backend systems in Python, including encryption, key management, sensitive-data controls, credential protection, tenant isolation, authentication, signing, and token handling. Own projects end to end from investigation and architecture through implementation, migration, staged rollout, observability, and recovery. The role requires applied cryptography, strong trust-boundary judgment, and experience safely evolving systems handling sensitive or regulated data across cloud, VPC, and on-premises deployments.

Own enterprise customer accounts from onboarding through renewal and expansion. Monitor customer health, usage, and outcomes; conduct QBRs; drive adoption and growth; support integrations, workflow design, launches, and training; maintain CRM and billing records; resolve issues cross-functionally; advocate for customers; and build relationships with technical and executive stakeholders.

Lead development of high-performance Rust parsers, compilers, automata, indexes, and data structures for structured language-model generation. Optimize decoding-loop performance through profiling and benchmarking, integrate Python bindings and C++/CUDA components into inference engines, collaborate across teams, and maintain production-quality code through testing and CI/CD.

Own the full B2B SaaS sales cycle, from prospecting through negotiation and close, while meeting quotas and acquiring automotive dealership customers. Present AI solutions and ROI cases to executives, build pipeline through cold outreach, expand accounts through cross-selling and upselling, and collaborate with Client Success and Solutions Engineering. The role requires technical aptitude, complex deal experience, strong negotiation skills, and comfort working in an ambiguous early-stage startup.