Top Tech Jobs & Startup Jobs in Chicago, IL

Own PushPress’s data platform, including ingestion, orchestration, cloud warehouse performance, governance, privacy, data quality, monitoring, and AI-ready data foundations. Build reliable pipelines integrating product, payment, and third-party data; establish data contracts, access controls, auditability, and semantic definitions; support real-time analytics and trustworthy reporting. Partner with Engineering, Data, and AI teams while maintaining infrastructure, incident response, documentation, and operational runbooks.

Configure and quality-assure claims administration systems for group onboarding and renewals. Support vendor implementations, testing, migrations, data imports and exports, integrations, and troubleshooting of system and data-feed issues. Collaborate with operations, implementation, renewal, development, project management, and external vendors while maintaining security, governance, audit, and HIPAA compliance requirements.

Leads customer engagements and large-scale analytics projects from inception through delivery, ensuring measurable business value, quality, budgets, and timelines. Builds customer relationships, translates needs into analytics solutions, supports renewals and expansions, and coordinates with product, engineering, and data science teams. Also supports solution architecture, pre-sales demonstrations, proof-of-concept implementations, technical use-case development, and customer conferences. Presents complex insights to technical and nontechnical stakeholders.

Create, edit, and proofread B2B and B2C marketing content across websites, email, campaigns, thought leadership, sales enablement, events, presentations, video scripts, social media, and paid media. Translate complex information into clear messaging, collaborate with cross-functional stakeholders, apply SEO and AEO best practices, use generative AI responsibly, manage multiple deadlines, and ensure final content quality and brand consistency.

Own enterprise customer relationships from onboarding through adoption, value realization, renewal, and expansion. Lead implementation projects, executive business reviews, success planning, demos, and customer escalations. Build workflows, reports, and dashboards, while handling API integrations, SQL queries, and Python scripting. Collaborate with Solutions Architecture, Engineering, Product, Sales, and Account Executives to drive customer ROI, advocate for customer priorities, and support renewals and growth.

Lead CluePoints’ alliance and channel strategy across technology partners, systems integrators, consultancies, and regional resellers. Build partner-sourced revenue, develop channel programs, enable partners, manage complex commercial relationships, and collaborate with Sales, Marketing, Product, and Services. The role will establish partnerships in markets including Japan, India, and Europe, while eventually building and leading a partnerships team.

Provide empathetic, timely support to customers, resolve inquiries and issues, document interactions, and escalate complex problems to appropriate teams.

Own regional capture supply for an embodied AI data platform by selecting target markets, building partner pipelines, negotiating commercial agreements, setting capacity plans, and managing partners through ramp-up. The role requires developing a regional playbook from scratch, securing high-volume capture partners, monitoring quality and output, growing successful relationships, reporting market insights, and traveling regularly across the region.

Build four documented Python and Jupyter cookbook recipes demonstrating Arango use cases, including LLM, RAG, embeddings, vector search, and graph database applications. Select use cases, explain business value, develop working code, incorporate engineer feedback, and publish contributions to GitHub. Collaborate remotely with a distributed product and engineering team.

Create, solve, review, and validate coding-heavy machine learning tasks for AI training. Build and optimize models, training and inference workflows, data pipelines, evaluation systems, and reproducible Python workflows. Diagnose numerical and system-level failures, improve memory use and throughput, and verify technical correctness while working with coding agents.