Top Tech Jobs & Startup Jobs in Chicago, IL

Analyzes computer systems and business processes, gathers and validates stakeholder requirements, models workflows using BPMN or UML, and uses SQL for data analysis and troubleshooting. The role supports process optimization, technical issue resolution, virtual collaboration, and validation of AI training data and scenarios for customer projects.

Provides empathetic, efficient customer support across multiple channels; documents interactions in CRM software; analyzes issues and proposes solutions; applies product knowledge to educate users; shares customer feedback and sentiment trends; develops support documentation; and supplies scenario-based input to train AI systems. Requires at least three years of professional customer support experience, strong communication and problem-solving skills, CRM proficiency, and experience managing complex cases.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Conduct quantitative and qualitative research, analyze complex business scenarios, gather requirements, and synthesize stakeholder perspectives into actionable recommendations. Evaluate data using tools such as Excel or SQL, identify process improvements, and produce clear reports, memos, business cases, and documentation. Collaborate with stakeholders through written communication and contribute analytical content to help train AI systems.

Evaluate and annotate AI-generated outputs involving CRM workflows, sales processes, and automation logic. Apply rubrics consistently, assess CRM data and user interactions, document sales operations practices, identify process improvements, and provide actionable feedback to AI development stakeholders. The role requires hands-on CRM and sales operations expertise, experience with CRM platforms, and prior paid human data work such as annotation, labeling, RLHF, or model evaluation.

Design, simulate, verify, and validate analog, digital, power, mixed-signal, or RF circuits for an AI training project. Translate requirements into schematics, netlists, HDL, models, and simulation inputs; automate workflows with Python; analyze electrical results; perform corner and Monte Carlo analyses; compare simulations with physical measurements; troubleshoot hardware and review AI-generated circuit solutions. Requires real fabricated or shipped circuit-design experience and command-line or programmatic EDA expertise.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

Design, build, and maintain scalable big data pipelines, architectures, distributed databases, and storage systems. Use Python and frameworks such as Hadoop, Spark, or Flink for data integration, transformation, and processing. Ensure system performance, availability, security, governance, and data quality while collaborating with cross-functional teams and documenting technical solutions.

Develop and maintain scalable Java backend systems using Spring Boot and microservices architecture. Collaborate with customer teams, review specifications, write clean code, participate in code reviews, document solutions, and troubleshoot and optimize backend performance, reliability, and security. The role also contributes technical expertise to training next-generation AI systems, though prior AI experience is not required.

Develop and maintain backend services and RESTful APIs using C# and .NET. Design and optimize MySQL schemas and queries, troubleshoot production and staging issues, improve performance and scalability, document architecture, and uphold code quality and security. Collaborate with cross-functional teams in a fully remote environment while contributing to development best practices and continuous improvement.