OpenAI

DevOps Engineer

• Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development.
• Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability.
• Develop, validate, and apply package reliability models and lifetime-prediction methodologies for assembly, qualification, and product operating conditions.
• Evaluate and recommend package architectures, structural designs, materials, and assembly processes to maximize reliability performance and manufacturing robustness.
• Predict electromigration lifetime of package interconnects under product-specific current, temperature, workload, duty-cycle, and PCB boundary conditions.

Advanced Packaging Reliability Engineer

Full-stack Engineer

• Design and build scalable, reliable, and secure infrastructure platforms that power OpenAI products
• Evolve cloud infrastructure abstractions that enable rapid product development across teams
• Architect systems to support significant growth, performance, and operational complexity
• Improve server orchestration, networking, distributed systems reliability, and infrastructure security posture
• Influence technical direction and infrastructure strategy across multiple teams
• Partner closely with product, research, and engineering teams to align infrastructure with evolving needs
• Own operational excellence, including participation in on-call rotations, incident response, and production readiness
• Mentor engineers and raise the overall technical bar of the organization
• Contribute to a culture of high ownership, low ego, and thoughtful collaboration

Software Engineer, Infrastructure, Consumer Devices

Data Engineer

• Define the target architecture for customer, account, contact, lead, opportunity, activity, campaign, and support data.
• Assess and improve Salesforce data across the lead-to-support lifecycle.
• Design canonical data models, entity relationships, identity-resolution rules, and system-of-record definitions.
• Lead data-cleansing and remediation initiatives, including deduplication, normalization, enrichment, validation, and historical cleanup.
• Establish matching, merging, and survivorship rules for people, companies, accounts, and related records.
• Architect integrations between Salesforce, data warehouses, operational systems, support platforms, and third-party data providers.
• Define standards for field definitions, lifecycle stages, ownership, metadata, lineage, retention, and access controls.
• Implement automated monitoring for data quality, completeness, freshness, consistency, and integration failures.
• Improve the flow of data between marketing, sales, customer success, and support systems.
• Evaluate third-party data sources and define how external data should be matched, validated, and incorporated into enterprise systems.
• Partner with Business Systems, Revenue Operations, Data Engineering, Analytics, Security, and business stakeholders to translate operational requirements into durable technical solutions.
• Produce architecture diagrams, data dictionaries, integration specifications, governance documentation, and implementation guidance.
• Provide technical leadership and guide teams through complex data architecture and system-design decisions.
• Support and improve integrations involving Salesforce and go-to-market data platforms such as Clay, PitchBook, ZoomInfo, HG Insights, Cognism, Harmonic, and Meticulate.

Enterprise Application Data Architect, GTM Systems

Engineering Manager

• Lead and grow a team of engineers responsible for complex, high-impact deployments of OpenAI technology in sensitive environments.
• Own end-to-end delivery outcomes across prototype, pilot, production launch, and ongoing operation.
• Partner directly with senior customer stakeholders, technical teams, and implementation partners to scope work, sequence delivery, and remove blockers.
• Set and maintain a high bar for architecture, code quality, testing, observability, reliability, security, and operational readiness.
• Translate field learnings into reusable tools, playbooks, reference architectures, product requirements, and roadmap feedback.
• Help the team make crisp tradeoffs between speed, quality, security, safety, and customer-specific needs.
• Serve as a technical escalation point for deployments where ambiguity, urgency, or mission sensitivity is high.
• Coach engineers on technical judgment, customer communication, prioritization, and operating calmly under pressure.
• Build team mechanisms that let the group scale without adding unnecessary process or complexity.

Engineering Manager – Sensitive Deployments

Engineer

• Define and develop power testing automation to evaluate system behavior across a range of workloads and operating conditions.
• Measure subsystem-level power consumption using power breakout probes and other lab instrumentation.
• Develop and execute power characterization tests spanning basic workloads, complex mixed-use scenarios, and representative day-of-use experiences.
• Partner closely with Electrical Engineers to identify opportunities to improve system power efficiency.
• Collaborate with software engineering teams to optimize energy usage in scenarios that impact battery life, device temperature, charging performance, and overall user experience.
• Define repeatable power benchmarks and measurement methodologies to assess launch readiness and track performance throughout the product lifecycle.

System Power Engineer, Consumer Devices

• Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior.
• Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools.
• Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack.
• Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle.
• Measure, report, and track metrics including system responsiveness, memory utilization, cold boot performance, long-term stability, and behavior under constrained conditions such as thermal limits and low battery states.
• Investigate field performance regressions and drive issues to resolution using data-driven analysis.

System Performance Engineer, Consumer Devices

Account Executive

• Manage ~dozen key accounts in the Financial Services Industry, developing and executing strategies for a comprehensive account plan.
• Lead our enterprise prospects’ journeys from consideration to successful deployment.
• Partner with solutions and research engineering to build and execute complex customer programs and projects.
• Own a consumption revenue target.
• Manage consumption revenue forecasts.
• Analyze key account metrics to create reports and provide insights to internal and external stakeholders.
• Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and other corporate strategies.
• Collaborate with solutions, marketing, communications, business operations, people operations, finance, product management, and engineering.
• Support the recruitment and onboarding of other teammates.
• Support the development of company culture.

Account Director, FSI

Systems Engineer

• Build Salesforce solutions for ads GTM: Develop user experiences, objects, automations, and guardrails that help Ads Sales and Operations manage advertisers, opportunities, insertion orders, campaign readiness, approvals, and launch handoffs with high data quality.
• Engineer integrations across the ads stack: Connect Salesforce with ads platforms, product catalogs, pricing/rate-card systems, data warehouses, billing tools, measurement workflows, CLM, and e-signature systems so advertiser and campaign data stays accurate and auditable.
• Test, troubleshoot, and document: Resolve production issues quickly, strengthen observability, and maintain clear documentation aligned with ads operations, financial controls, privacy requirements, and deployment best practices.
• Partner cross-functionally: Collaborate daily with Ads Sales, Ads Operations, Product, Finance, Legal, Engineering, and GTM teams to translate ambiguous ads-business needs into durable Salesforce-based solutions.

Salesforce Ads Systems Engineer

Program Manager

• Work closely with research to understand data needs and define acquisition priorities and timeline that are aligned with our research roadmap.
• Translate research objectives into clear technical requirements and operational plans, ensuring data workflows, timelines, and quality standards are executed to the highest quality standards.
• Lead vendor and partner engagements for data sourcing – including evaluating suppliers, negotiating agreements, and managing delivery.
• Establish and maintain metrics for data quality, throughput, efficiency, and overall program performance, ensuring visibility to leadership and cross-functional partners.
• Identify gaps in our data ecosystem and proactively drive initiatives to strengthen our data acquisition and creation capabilities over time.

Program Manager, Foundations Data and Operations

Operations

• Participate in an on-call rotation and serve as the active incident lead during live incidents and urgent escalations.
• Own alert intake and triage process across support, safety, customer, and service-impacting issues.
• Assess severity, determine scope and impact, and initiate the appropriate response path.
• Page and coordinate Engineering, Infrastructure, Support Delivery, Product, Legal, Policy, Go-To-Market, and other teams as needed.
• Lead incident response calls, manage timelines, clarify roles, and keep responders focused and unblocked.
• Set internal guidelines for incident communications to all users, including enterprise customers, and own internal updates, executive briefings, customer-facing updates, and external status page updates where required.
• Maintain situational awareness across all customer-facing incidents and parallel workstreams, ensuring the response remains coordinated and customer impact is understood.
• Create and operate the process for monitoring, processing, mitigating, and resolving critical escalations, including formal closure and handoff.
• Identify root causes behind incidents and escalations, lead retrospectives, and coordinate corrective action with accountable teams.
• Track corrective actions to closure and ensure follow-through is focused on the best possible customer outcome.
• Identify recurring operational issues, escalation patterns, and product or process gaps.
• Partner with Engineering, Infrastructure, Product and Support leaders to stay ahead of customer-facing incidents, reduce repeat issues, and improve readiness.
• Improve incident response processes, severity frameworks, playbooks, tooling, reporting, and automation.
• Build a durable operating model for incidents and escalations as OpenAI scales globally.

Lead, Incidents & Escalations, User Operations

Financial Planning and Analysis

• Own full-stack product features from user experience and frontend implementation through backend services, data models, deployment, and observability.
• Build polished, accessible, and performant interfaces for account connection, dashboards, insights, and conversational workflows.
• Design APIs and backend systems that safely ingest, normalize, and serve financial data.
• Build resilient integrations that handle synchronization, data freshness, partial failures, permissions, and user consent.
• Bring new AI capabilities into production while prioritizing grounding, accuracy, transparency, and user control.
• Establish architecture, performance standards, testing practices, and operational safeguards for a fast-growing product area.
• Debug and improve complex behavior across client, server, infrastructure, and external integrations.
• Use qualitative feedback, product metrics, and experiments to improve user outcomes without compromising clarity or trust.
• Collaborate across disciplines to turn ambiguous product opportunities into simple, reliable experiences.

Full Stack Engineer, ChatGPT Finances

Data Scientist

• Define and lead fairness and bias-testing strategies for AI-assisted People processes, models, agents, and decision-support systems from development through deployment and ongoing monitoring.
• Design rigorous algorithmic audits and validation studies, including adverse-impact analysis, subgroup and intersectional evaluation, error-rate analysis, calibration, measurement invariance, reliability, criterion-related validity, and sensitivity testing.
• Identify the appropriate fairness criteria for each use case, evaluate tradeoffs among competing definitions of fairness, and clearly document the assumptions, limitations, and residual risks of each approach.
• Evaluate end-to-end human-AI decision systems, including model outputs, user behavior, human overrides, escalation pathways, and whether AI assistance changes the quality, consistency, or equity of decisions.
• Develop evaluation approaches for generative and agentic AI, including test-set design, counterfactual testing, behavioral evaluation, human-rating studies, robustness testing, and analysis of disparate performance across populations and contexts.
• Investigate the sources of observed disparities, including data representation, label and measurement bias, proxy variables, model design, decision thresholds, workflow design, and differential adoption or usage.
• Partner with engineering, People Operations, Legal, Privacy, Security, and People Systems teams to recommend and evaluate mitigations such as data improvements, model changes, threshold adjustments, workflow redesign, monitoring controls, and additional human oversight.
• Build scalable fairness-evaluation infrastructure, including reusable datasets, automated validation pipelines, regression tests, monitoring systems, self-service tools, and standardized reporting.
• Establish research and documentation standards for fairness test plans, dataset and model documentation, validation reports, limitations, monitoring plans, and decision records.
• Translate complex findings into concise, decision-ready narratives, helping leaders understand the significance of identified risks, the strength of the evidence, available mitigation options, and remaining uncertainty.

People Research Data Scientist, AI Fairness, Bias

Content Marketing Manager

• Own the health and integrity of the Customer Education content portfolio, including lifecycle, governance, discoverability, reuse, and meaningful gaps.
• Ensure customer-facing teams can confidently find and use the right education resources at the right time.
• Run the team’s operating rhythm across priorities, ownership, timelines, dependencies, decisions, launch readiness, and follow-through.
• Turn ambiguous cross-functional initiatives into clear plans, workflows, responsibilities, and decision points.
• Design scalable processes and handoffs for how education programs are created, launched, maintained, distributed, and measured.
• Translate team and business needs into practical system requirements and partner across teams to bring solutions to life.
• Identify operational risks, portfolio gaps, duplicated effort, and breakdowns in execution before they become larger problems.
• Use AI deeply to automate repeatable work, strengthen quality control, synthesize inputs, and create better operating leverage.

Customer Education, Content & Systems Operations Lead

• Manage a portfolio of startups accounts, developing and executing strategies for a comprehensive account plan.
• Partner with solutions architects to drive successful technical engagements with startups, accelerating their product development process.
• Own a consumption revenue target.
• Manage consumption revenue forecasts.
• Analyze key account metrics to create reports and provide insights to internal and external stakeholders.
• Collaborate with solutions, marketing, communications, business operations, people operations, finance, product management, and engineering.
• Serve as an advocate for improving the startup experience building with OpenAI, synthesizing product feedback from insights captured from our work with startups.
• Closely monitor the industry landscape and startup landscape and contribute to corporate strategies.
• Support the recruitment and onboarding of other teammates.
• Support the development of company culture.

Account Director, Startups

• Own and improve the customer trust operating model with other org members and partner teams, including intake, triage, escalations, SLAs, metrics, and quality review.
• Support strategic customer trust needs, including security questionnaires, customer calls, Trust Center updates, and high-priority deal support.
• Partner with Product, Security, Legal, Privacy, and GTM teams to prepare accurate, approved trust materials for launches and regulated product changes.
• Build reusable customer-facing narratives, FAQs, evidence paths, and whitepapers that reduce one-off work while keeping claims controlled.
• Ensure external security and compliance claims are supported by internal processes and controls.
• Ensure product launches support our external security and compliance narrative; scale launch reviews to ensure GRC is not a bottleneck.
• Develop data handling guidance as needed to provide product teams a paved path consistent with our external commitments.
• Use automation and AI-native workflows across internal and external tooling, Codex, and related systems to improve speed and consistency.
• Turn recurring customer discovery into reusable content, product feedback, evidence improvements, and control-gap signals.