Top Artificial Intelligence Jobs in Pittsburgh, PA

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.

Develop and manage affiliate partnerships for an AI-powered dialer targeting SMBs: recruit affiliates and influencers, design commission structures and materials, onboard and support partners, monitor performance, optimize ROI, and align affiliate efforts with overall marketing strategy while ensuring compliance.

Lead and execute high-volume (10,000+/month) outbound email campaigns for US SMBs: craft copy and subject lines, segment lists, optimize deliverability, analyze performance, and align messaging with sales and marketing.

The Senior Sales Engineer partners with sales teams and customers to lead technical evaluations, deliver compelling product demonstrations, troubleshoot common issues, connect business needs to technical solutions, and manage complex technical engagements. The role requires strong cloud and Terraform knowledge, familiarity with software development or DevOps, ability to respond to RFIs and RFPs, communicate customer requirements to Engineering, represent the product at events, and travel throughout the assigned territory.

Leads Hello Heart’s enterprise marketing strategy and team, driving B2B demand generation, qualified pipeline, positioning, messaging, sales enablement, partner marketing, events, and product launches. Partners with Sales, Customer Success, Partnerships, Product, and BDRs to support commercial growth across employers, consultants, health plans, and strategic partners. Owns campaign performance measurement, KPIs, experimentation, and optimization while embedding AI into marketing strategy and operations.

Develop and maintain MuleSoft integrations while migrating enterprise applications from Oracle Service Bus. Design, code, test, debug, and optimize APIs and integration solutions using Anypoint Platform, DataWeave, REST, SOAP, XML, and JSON. Collaborate with Scrum teams, stakeholders, infrastructure, security, and business teams to define integration requirements, establish standards, create reusable assets, support deployments, resolve complex issues, and drive sustainable platform adoption.

Lead development of Chariot’s claims processing pipeline and CRM systems, transforming manual scripts into reliable, observable production infrastructure. Build claimant and law-firm workflows, fraud detection and verification stages, dashboards, integrations, internal tooling, and AI agent harnesses. Own product decisions, recruit and develop engineers, and establish pipeline reliability. The role requires staff-level software ownership, early-stage startup experience, and proficiency with Go and AWS.

Engineering Lead responsible for Chariot Claims’ consumer acquisition and claim-filing funnel, claimant communications, evidence and signature collection, dispute scheduling, and payment disbursement systems. The role owns technical direction, rapid experimentation, platform foundations, AI-native tooling, and team hiring and development. Candidates should have staff-level production software experience, strong product judgment, early-stage startup experience, and familiarity with payments or money-movement systems.

Lead the engineering team building Chariot’s AI claims platform, including agent systems for case origination and claims matching, human-in-the-loop review, evaluation infrastructure, and scalable AI performance. The role owns product decisions, internal tooling, cost efficiency, and production reliability while recruiting and developing full-stack and ML engineers. Experience with production software, end-to-end product ownership, early-stage startups, and modern LLM systems is valued.

Design and scale batch and streaming data pipelines, ETL/ELT workflows, data models, warehouses, quality frameworks, dashboards, and AI/ML feature pipelines. Automate reporting and analytics while collaborating with product, engineering, and operations teams. The role also includes internal consulting practice participation, thought leadership, client case studies, and contribution to digital transformation initiatives.

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.

Responsible for sourcing and closing net-new enterprise accounts in the Southeast, developing territory strategies, building executive sponsorship and champions, running value-driven sales cycles and tight POCs, collaborating with internal teams, and meeting ARR targets through data-driven ROI justification and repeatable sales processes.

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.