Bengaluru, KarnatakaNoida, Uttar Pradesh
Job Summary

We are seeking a technically deep, creativity-driven AI Deployment Engineer who is already a power user of AI coding tools and passionate about pushing the boundaries of developer productivity. This is a highly cross-functional role that blends technical architecture, product strategy, and customer-facing leadership. Partner directly with engineering leaders and hands-on builders to design, validate, and scale advanced AI workflows, often using Codex to prototype and build the very demos, integrations, and automations customers ultimately adopt.

Key Responsibilities
Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows.
Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout.
Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of your development process.
Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely.
Contribute technical content including examples, guides, patterns, and best practices for OpenAI EBU Cookbook to help accelerate work with Codex.
Gather high-fidelity product insights from real customer deployments and translate them into transparent product proposals and model feedback for internal teams.




Influence customer strategy and decision-making by framing how AI coding tools fit into their SDLC, technical roadmap, and organizational workflows.
Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.
Skill Requirements
Have 5+ years of technical consulting, post-sales engineering, solutions architecture, or similar experience working directly with customers.
Are an active power user of AI coding tools and have deeply customized your own developer workflow; you have a point of view on what makes engineers more productive.
Enjoy building scrappy, high-signal demos, integrations, and prototypes that clearly articulate what Codex can enable, often using Codex to accelerate your own development process.
Have experience delivering large, high-impact workshops or technical training to engineering teams and know how to craft sessions that are engaging, hands-on, and outcomes-driven.
Have contributed technical guides, patterns, or examples publicly and care about clarity, pedagogy, and community impact.
Communicate complex technical concepts in clear, persuasive written and verbal form especially when helping customers make strategic decisions about where and how to apply AI.
Are excited by ambiguous,



rapidly evolving problem spaces and enjoy iterating toward novel solutions hand-in-hand with customers.
Care about customer success, reliability, safety, and operational excellence as much as you care about technical ingenuity.
Other Requirements
Familiarity with OpenAI’s models, APIs, Codex, Codex Security, Daybreak, or related cyber capabilities.
Experience working with security-product companies, global systems integrators, or cybersecurity partners.
Depth across application security, cloud security, identity, secure SDLC, vulnerability management, detection and response, or attacker tradecraft.
Experience developing repeatable field assets, technical enablement, or product feedback mechanisms across multiple regions.

Preferred Qualifications

Master’s degree in computer science, Artificial Intelligence, Data Science, Engineering, or a related field, or relevant cloud, AI, security, architecture, or data certifications.
Experience with Azure, AWS, or Google Cloud; enterprise data platforms; vector databases and search; API management; containers and Kubernetes; DevSecOps; and MLOps/LLMOps toolchains.
Experience in consultative or presales solutioning, regulated-industry environments, architecture governance, and creation of reusable reference architectures, accelerators, evaluation suites, and bid-response artifacts.
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