AI Deployment Engineer

Openai·Remote(New York City)

Software Development

WFA Digital Insight

As the demand for AI-powered solutions continues to skyrocket, with over 70% of businesses expected to adopt some form of AI by 2027, the need for skilled professionals who can bridge the gap between technology and business has never been more pressing. OpenAI, a pioneer in AI research and deployment, is seeking an AI Deployment Engineer to join its team in New York City, offering a unique chance to work at the forefront of Generative AI applications. With the hybrid work model gaining traction, this role offers the perfect blend of in-office collaboration and remote flexibility, ideal for those looking to balance work and personal life. Candidates should be prepared to showcase not only their technical prowess but also their ability to communicate complex ideas to both technical and non-technical stakeholders.

Job Description

About the Role

The AI Deployment Engineering team at OpenAI plays a crucial role in ensuring the safe and effective deployment of Generative AI applications for a wide range of customers, from developers to large enterprises. As an AI Deployment Engineer, you will be part of a team that acts as trusted advisors and technical partners to customers, helping them navigate their AI adoption strategy post-sale. The team's mission is to develop a strong backlog of GenAI use cases tailored to each customer’s industry and drive these initiatives from prototype to production through hands-on technical guidance and partnership.

The role of an AI Deployment Engineer is multifaceted, requiring a deep understanding of both the technical aspects of AI deployment and the business needs of the customers. You will work closely with senior leaders and technical teams within customer organizations to establish GenAI roadmaps, strategies, prioritize high-value use cases, and guide projects from early prototyping through enterprise-grade production deployments. This position demands a holistic view of each customer’s architecture and operations, designing solutions that leverage ChatGPT, OpenAI APIs, and the broader ecosystem of tools and services.

What You Will Do

Serve as the primary technical subject matter expert post-sale for a portfolio of customers, embedding deeply with them to design and deploy GenAI solutions.
Engage with senior business and technical stakeholders to identify, prioritize, and validate the highest-value GenAI applications in their roadmap.
Accelerate customer time to value by providing architectural guidance, building hands-on prototypes, and advising on best practices for scaling solutions in production.
Maintain strong relationships with leadership and technical teams to drive adoption, expansion, and successful outcomes.
Contribute to open-source resources and enterprise-facing technical documentation to scale best practices across customers.
Share learnings and collaborate with internal teams to inform product development and improve customer outcomes.
Codify knowledge and operationalize technical success practices to help the Solutions Architecture team scale impact across industries and customer types.
Collaborate with the Sales team to identify new business opportunities and with the Solutions Engineering team to develop and refine GenAI solutions.
Participate in the development of training programs to enhance the skills of the Solutions Architecture team.
Provide feedback to the Product team on customer needs and market trends to influence the development of new features and products.

What We Are Looking For

5+ years of technical consulting, post-sales engineering, solutions architecture, or similar experience working directly with customers.
Strong communication skills, with the ability to explain technical and business concepts clearly to executive and practitioner audiences alike.
Experience leading complex deployments of Generative AI or traditional machine learning systems, ideally including infrastructure and network architecture considerations.
Hands-on proficiency in languages like Python, JavaScript, or similar, and comfort building prototypes or proofs of concept.
Ability to take end-to-end ownership of challenges, proactively acquiring new skills or knowledge as needed to drive success.
A humble, collaborative mindset with an eagerness to support teammates and customers alike.
Ability to thrive in fast-paced environments, adeptly managing multiple workstreams and prioritizing for the highest customer impact.
Strong problem-solving skills, with the ability to analyze complex issues and develop creative solutions.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.

Nice to Have

Experience with DevOps tools such as Docker, Kubernetes, or Jenkins.
Knowledge of agile development methodologies and version control systems like Git.
Familiarity with data engineering and data science concepts, including data pipelines and data visualization.
Certification in AI, machine learning, or a related field.
Experience working in a hybrid or fully remote work environment.

Benefits and Perks

Competitive salary and benefits package.
Opportunity to work with cutting-edge AI technology and contribute to its development.
Collaborative and dynamic work environment with a team of experienced professionals.
Flexible work arrangements, including a hybrid work model with 3 days/week in the office.
Relocation assistance for new employees.
Access to professional development opportunities and training programs.
Recognition and reward for outstanding performance and contributions.
Comprehensive health insurance and retirement savings plan.
Generous PTO and holidays to ensure a healthy work-life balance.

How to Stand Out

Ensure you have a strong foundation in programming languages such as Python or JavaScript, as well as experience with cloud platforms.
Highlight your ability to communicate complex technical concepts to non-technical stakeholders in your resume and cover letter.
Prepare to talk about your experience with AI and machine learning deployments, including any challenges you faced and how you overcame them.
Demonstrate your problem-solving skills by walking the interviewer through your thought process when approaching a complex technical issue.
Show enthusiasm for the field of AI and a willingness to continuously learn and adapt to new technologies and methodologies.
Be prepared to discuss your experience working in a team environment and collaborating with cross-functional teams.
Consider creating a portfolio of your work, including prototypes or proofs of concept you’ve developed, to share with the interviewer.

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