Scale Engineer

Forward Deployed Engineer - Sydney

Forward Deployed Engineer · Senior · Full Time

Sydney, AustraliaAUD 180k – 280k3mo ago
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Role

What you'll do.

Forward Deployed Engineer at OpenAI leads end-to-end production deployments of frontier AI models alongside strategic customers in Sydney, owning discovery through rollout. This senior technical role requires 5+ years of full-stack engineering experience with demonstrated expertise in customer-facing complex system deployments, LLM integration, and production-grade Python or JavaScript development. Success demands exceptional communication across engineering and executive stakeholders, rapid decision-making in ambiguous environments, and deep understanding of how generative model behavior impacts product adoption and user workflows.

Responsibilities

  • End-to-End Deployment Ownership: Own complete delivery lifecycle of production AI model deployments from initial customer discovery and requirements gathering through prototype development, system implementation, comprehensive testing, and stable production rollout. Drive milestone planning, resource coordination, and go-live execution.
  • Full-Stack System Architecture and Development: Design and build complete end-to-end systems that integrate frontier OpenAI models into customer environments, including frontend interfaces, backend APIs, data pipelines, and infrastructure components. Write production-grade code across technology stacks and ensure system reliability and performance.
  • Customer Engagement and Adoption Leadership: Embed closely within customer technical and domain teams to understand business needs, establish trust, and guide successful adoption of deployed systems. Provide technical guidance, conduct training sessions, and maintain ongoing support to maximize product value realization and workflow impact.
  • Technical Scoping and Planning: Conduct thorough technical discovery with customers to identify requirements, constraints, and risks. Create detailed scopes of work, establish realistic delivery timelines, identify dependencies and blockers early, and adjust plans dynamically to balance speed, quality, and scope while protecting delivery commitments.
  • Quality Trade-off Management: Make strategic decisions balancing scope completeness, delivery velocity, and system quality based on business priorities and risk assessment. Establish quality standards appropriate to production environments, implement comprehensive testing strategies, and protect critical reliability standards while maintaining deployment momentum.
  • Direct Contribution and Code Implementation: Contribute directly to code implementation when technical progress or clarity requires hands-on engineering work. Remove implementation blockers, unblock team members, and demonstrate technical feasibility through prototype development or spike work.
  • Systematic Knowledge Codification: Capture working patterns, successful approaches, and lessons learned from deployments into reusable tools, runbooks, playbooks, and building blocks. Document best practices to accelerate future deployments and multiply team effectiveness across the growing customer base.
  • Model and Product Feedback Integration: Gather detailed field observations about model behavior, failure modes, customer pain points, and workflow gaps from production deployments. Synthesize feedback into actionable insights and communicate findings to Research and Product teams to inform model training priorities, feature development roadmaps, and go-to-market strategy.
  • Cross-Functional Team Coordination: Lead communication and coordination across Product, Research, Partnerships, GRC, Security, and GTM teams to align deployment objectives with organizational priorities. Escalate and resolve cross-functional blockers, ensure compliance and security requirements are met, and maintain visibility into deployment status and risk factors.
  • Team Momentum and Execution Excellence: Maintain clarity through comprehensive communication, transparent status updates, and decisive action. Build team confidence through sound decision-making, follow-through on commitments, and calm judgment during high-pressure situations. Create psychological safety that enables the team to move quickly without unnecessary delays or second-guessing.

Qualifications

What we look for.

Technical

  • Python Programming

    Production-level proficiency in Python for backend system development, API creation, and data processing workflows.

  • JavaScript/TypeScript

    Strong capability in JavaScript or TypeScript for frontend development and full-stack system implementation.

  • Full-Stack Development

    Ability to architect and implement complete systems spanning database, backend services, and frontend interfaces.

  • LLM API Integration

    Experience integrating and working with large language model APIs and generative AI platforms in production systems.

  • Version Control and Collaboration

    Proficiency with Git and modern development workflows including code review, CI/CD, and collaborative development practices.

Education

  • Bachelor's Degree in Computer Science or Related Field

    Formal degree in Computer Science, Software Engineering, or equivalent technical discipline. Equivalent professional experience may substitute for formal education.

Experience

  • 5+ Years Professional Engineering Experience

    Minimum five years of professional software engineering or technical deployment experience demonstrating progression in complexity and responsibility.

  • Customer-Facing Technical Work

    Significant experience working directly with customers or end-users on technical implementations, including understanding customer needs, managing expectations, and ensuring adoption.

  • Complex System Delivery

    Demonstrated success scoping, designing, and delivering complex technical systems in fast-moving or ambiguous environments with shipped production outcomes.

  • LLM or Generative Model Systems

    Hands-on experience building or deploying systems powered by large language models or contemporary generative AI models, with understanding of model behavior implications for products.

  • Decision-Making Under Pressure

    Proven ability to make sound technical and strategic decisions rapidly in high-stakes scenarios where perfect information is unavailable, maintaining team confidence and delivering results.

Skills

Required

  • Full-Stack Software Development

    Demonstrated proficiency writing and reviewing production-grade code across both frontend and backend systems using Python, JavaScript, or equivalent modern stacks. Must have shipped multiple full-stack systems to production with responsibility for system architecture and code quality.

  • Large Language Model (LLM) Integration

    Hands-on experience building or deploying systems powered by large language models or generative AI models. Deep understanding of how model behavior, latency, throughput, and hallucination characteristics affect end-user product experience and customer workflows.

  • Customer-Facing Technical Leadership

    Proven ability to embed with customer engineering and domain teams, translate technical requirements into clear implementation plans, and guide customers through adoption. Experience scoping complex technical projects directly with stakeholders and managing expectations in fast-moving environments.

  • Complex System Design and Delivery

    Experience architecting and delivering complex, multi-component systems in production environments. Demonstrated ability to make scope and quality trade-offs, sequence work for maximum delivery velocity, and maintain production stability under pressure.

  • Ambiguous Problem-Solving

    Comfort operating in high-ambiguity environments without complete specifications or clear solutions. Ability to independently scope work, identify hidden requirements, remove blockers, and adjust plans dynamically while maintaining team momentum and delivery timelines.

  • Cross-Functional Communication

    Exceptional ability to communicate technical concepts clearly to diverse audiences including engineering teams, product managers, research scientists, and non-technical customer stakeholders. Proven track record of translating field feedback into actionable insights for product and research teams.

Preferred

  • Enterprise AI/ML Deployment

    Nice to have

    Experience deploying AI or machine learning systems in enterprise customer environments, including understanding compliance, security, and scalability requirements at production scale.

  • Generative AI Product Development

    Nice to have

    Background building products or systems leveraging generative AI technologies, with understanding of how to measure model performance, iterate on prompts, and optimize for user adoption.

  • RESTful API and Backend Architecture

    Nice to have

    Strong experience designing and implementing scalable backend systems, APIs, and microservices that support high-throughput production workloads.

  • Data Evaluation and Metrics

    Nice to have

    Experience designing and implementing evaluation frameworks, metrics, and feedback loops that drive continuous model and product improvement based on real-world production data.

  • Infrastructure and DevOps

    Nice to have

    Understanding of cloud deployment, containerization, CI/CD pipelines, and infrastructure-as-code practices that enable rapid and safe production releases.

Tech stack

Languages

PythonJavaScript/TypeScript

Frameworks

OpenAI API and SDKsReactFastAPI or DjangoNode.js/Express

Databases

PostgreSQLVector Databases (Pinecone, Weaviate)

Tools

Git and GitHubDocker and KubernetesCloud Platforms (AWS, Azure, GCP)Monitoring and Logging Tools

Other

LLM Evaluation and Testing FrameworksPrompt Engineering and Fine-TuningRAG and Knowledge Integration Patterns

Compensation

Pay and benefits.

Base·AUD 180,000 – 280,000

Equity·Stock options

Benefits

  • Hybrid Work Model

    Work three days per week in the Sydney office with flexibility to work remotely two days weekly, enabling strong team collaboration while maintaining work-life balance.

  • Relocation Assistance

    Comprehensive relocation support package for candidates relocating to Sydney, including moving costs, temporary housing, and transition support.

  • Equity Compensation

    Competitive equity package providing ownership stake in OpenAI and alignment with company long-term success.

  • Health and Wellness Benefits

    Comprehensive medical, dental, and vision insurance coverage with employer contribution toward premiums and preventive care programs.

  • Retirement Planning

    Superannuation contributions and retirement planning support aligned with Australian employment standards and regulations.

  • Professional Development

    Access to learning resources, conference attendance budgets, technical training, and mentorship from AI research and engineering leaders at OpenAI.

  • Paid Time Off

    Generous paid vacation policy and flexible time off to support work-life integration and employee wellbeing.

Process

Interview steps.

  1. 01

    Initial Screening Call

    Introductory conversation with a technical recruiter to discuss background, motivation for the role, and alignment with Forward Deployed Engineering principles. Focus on customer-facing experience, relevant deployment work, and AI/ML exposure.

  2. 02

    Technical Assessment

    System design interview evaluating ability to architect complex end-to-end systems integrating language models. Expect discussion of trade-offs between scale, latency, cost, and quality in production deployments. May include coding components assessing Python or JavaScript proficiency and understanding of API design.

  3. 03

    Customer Engagement Simulation

    Scenario-based interview assessing customer communication skills and ability to scope ambiguous technical requirements. Evaluate how you would approach customer discovery, manage expectations, guide adoption, and handle technical challenges in a customer-facing context.

  4. 04

    Deployment Experience Deep Dive

    Behavioral interview exploring past complex deployment projects, including how you scoped work, made trade-offs, coordinated teams, removed blockers, and handled pressure or unexpected challenges. Focus on outcomes, team impact, and lessons learned.

  5. 05

    LLM and AI System Knowledge

    Technical conversation evaluating understanding of large language model capabilities, limitations, and production considerations. Discuss experience building with generative models, understanding model behavior, and optimizing for user adoption and workflow impact.

  6. 06

    Leadership and Cross-Functional Collaboration

    Interview assessing ability to work effectively across diverse functional teams including Product, Research, Security, and GTM. Evaluate communication clarity, decision-making judgment under ambiguity, and ability to build consensus across organizational boundaries.

  7. 07

    Executive Interviews

    Conversations with Forward Deployed Engineering leadership and potentially senior leadership across OpenAI to assess cultural fit, leadership quality, and strategic thinking alignment. Opportunity to ask detailed questions about team dynamics, impact expectations, and career growth opportunities.

Full posting

Original listing.

About the team

OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.

About the role

Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams.

You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams.

This role is based in Sydney. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required.

In this role you will

  • Own technical delivery across multiple deployments from first prototype to stable production.

  • Build full-stack systems that deliver customer value and sharpen how we learn.

  • Embed closely with customer teams, understand their needs, and guide adoption of what you build.

  • Scope work, sequence delivery, and remove blockers early.

  • Make trade-offs between scope, speed, and quality; adjust plans to protect delivery.

  • Contribute directly in the code when progress or clarity depends on it.

  • Codify working patterns into tools, playbooks, or building blocks that others can use.

  • Share field feedback that helps Research and Product understand where the models succeed and where they can improve.

  • Keep teams moving through clarity and follow-through.

You might thrive in this role if you

  • Bring 5+ years of engineering or technical deployment experience that includes customer-facing work.

  • Have scoped and delivered complex systems in fast-moving or ambiguous environments.

  • Write and review production-grade code across frontend and backend using Python, JavaScript, or comparable stacks.

  • Have built or deployed systems powered by LLMs or generative models and understand how model behaviour affects product experience.

  • Simplify complexity and make fast, sound decisions under pressure.

  • Communicate clearly with engineers, product teams, and customer stakeholders.

  • Spot risks early and adjust without slowing down.

  • Model calm and judgment when the stakes are high.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

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At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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