Top Tech Jobs & Startup Jobs in Chicago, IL

Own G2’s security governance, risk, and compliance program, including policy management, customer security questionnaires, Trust Center operations, vendor risk, DSAR workflows, risk registers, and SOC 2 and ISO 27001 audits. Manage GRC tools and vendors, coordinate with Legal, Security, IT, Sales, auditors, customers, and executives, and deliver risk reporting, remediation oversight, and process automation as a senior individual contributor.

Partner with product teams to build data products, dashboards, and self-service AI/agent tooling. Own product metrics, run exploratory and ad-hoc analyses, improve data quality and governance, and translate analysis into clear recommendations to drive product OKRs.

Design, build, and ship agent-first AI products end-to-end. Implement production-ready agents using frontier models, ensure observability and quality via model-based evals and agent tracing, drive product definition with PMs/designers, and share agentic engineering practices to accelerate the team.

Leads development of agent evaluation systems that assess live software agents using trace data, rubrics, benchmarks, and LLM-as-a-judge techniques. Owns the evaluation platform’s full stack, creates reusable workflows and integrations, tracks emerging evaluation methods, and collaborates with data science teams. Manages and mentors engineers while promoting evaluation practices across agent-focused products.

Supports G2 Marketing’s AI fluency initiative by developing AI adoption deep-dives, diagnosing team readiness, tracking progress, maintaining assessment tools and dashboards, supporting cross-team workflows, building training materials, and documenting playbooks. The intern analyzes assessment data, validates use cases, coordinates curriculum rollout, gathers feedback, and helps marketing teams embed AI into daily workflows.

Lead G2’s experimentation practice across products and digital marketplaces. Design experimentation standards, causal inference methods, metrics, guardrails, and analysis approaches; partner with product and engineering to implement experimentation platforms and instrumentation. Build models, design auctions, ship production systems, evaluate modern statistical methods, and address marketplace interference and low-traffic constraints. Mentor data scientists and evangelize rigorous data science practices across the organization.

Own go-to-market strategy and hands-on growth execution for G2’s AI Solutions portfolio, from early beta validation through revenue and integration into G2.com. Responsibilities include defining audiences, positioning products, running acquisition and activation experiments, conducting user research, building pipeline, enabling Sales, monitoring competitive trends, and partnering with Product and Marketing teams. The role requires taking ambiguous, early-stage AI products from zero to revenue in a B2B SaaS environment.

Own and scale marketing-to-sales operations infrastructure across Salesforce, Marketo, Clay, Qualified, and related systems. Manage lead lifecycle architecture, routing, scoring, enrichment, deduplication, data quality, conversational marketing workflows, and funnel optimization. Partner with Marketing, Sales, SDRs, Business Systems, and vendors to improve pipeline quality, speed to lead, and sales efficiency. Implement AI-enabled automation, oversee tool budgets, and support system migrations and process governance.

Own marketing analytics, funnel and campaign reporting, lead scoring, routing, data reconciliation, and Marketing-to-Sales handoff workflows. Build dashboards, validate Salesforce and Marketo data, manage RingLead logic, troubleshoot routing issues, and perform recurring QA across go-to-market systems. Partner with BI and Data teams, identify optimization opportunities, present findings to leadership, and use AI tools to accelerate reporting and data-quality workflows.

Own the Data Solutions business end to end, including revenue, strategic client relationships, team leadership, and product direction. Source and close complex data deals with institutional investors, build predictable pipelines, guide pricing and forecasting, drive account adoption and expansion, coach sales and client support teams, and translate investor feedback into product roadmaps.