AI Deployed Engineer

AI Forward Deployed Engineer, Principal Consultant Travel component: up to ~30% customer-related travel About the Role We are seeking a highly skilled AI Forward Deployed Engineer to work directly with enterprise customers, helping them design, implement, and scale next-generation AI solutions. This role sits at the intersection of engineering, customer success, and strategic business outcomes. You will embed with client teams, translate their goals into technical architectures, and deploy cutting-edge generative AI systems that drive measurable value. The ideal candidate combines deep technical expertise in AI/ML with the ability to collaborate directly with business leaders, creative professionals, and technical stakeholders. You will serve as both an engineer and a strategic partner, ensuring AI adoption leads to tangible impact across customer organizations. Key Responsibilities • Customer Deployment & Integration • Work directly with enterprise clients to architect, build, and deploy AI solutions that integrate into their existing creative and business workflows. • Design and optimize large-scale AI pipelines (e.g., data ingestion, model deployment, fine-tuning, inference optimization). • Develop proof-of-concepts and scalable production systems that demonstrate the power of generative AI. • Collaborate & Innovate: work with Technical Architects, Engagement Managers, and Product teams to define customer requirements/use-cases, run technical workshops, co-create GenAI solutions. • Prototype Rapidly: build proof-of-concepts in days, iterate based on feedback, drive quick wins. UX/UI and prototyping skills are helpful. • Engineer End-to-End: design, build, and deploy full-stack applications / microservices integrating Firefly APIs, extensibility platforms, headless CMS, etc. • Bridge to Product: capture field-proven use cases and feed them back into the product & engineering roadmaps. • Automate & Scale: develop reusable components, CI/CD pipelines, governance & best practices for repeatable delivery. • Operate at Speed: work in fast-paced, evolving environments; own delivery sprints; adapt to changing trends. • Documentation / Knowledge Sharing: share playbooks, prompt patterns, internal tooling, etc. • Strategic Advisory • Translate customer business objectives into technical AI strategies and roadmaps. • Advise customers on how to adapt processes, governance, and adoption models for AI-driven outcomes. • Identify opportunities where AI can unlock new business models, workflows, or creative capabilities. • Engineering Excellence • Customize and extend foundation models through fine-tuning, prompt engineering, and domain-specific adaptation. • Build APIs, SDKs, and integration layers to connect AI systems with enterprise applications. • Ensure solutions meet enterprise standards for performance, reliability, security, and compliance. • Collaboration & Evangelism • Partner with product and research teams to provide customer feedback that informs model development and platform strategy. • Mentor client and partner engineers to accelerate adoption of AI technologies. • Act as a thought leader in customer workshops, executive briefings, and industry discussions. Qualifications Required: • 10+ years of experience in software engineering, machine learning engineering, or applied AI roles. • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow. • Strong understanding of large language models (LLMs), multimodal generative AI, and fine-tuning techniques. • Experience building scalable APIs, pipelines, and distributed systems for real-world AI deployments. • Excellent communication skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders. • Demonstrated success in customer-facing or forward-deployed engineering roles. Preferred: • Full-Stack Experience: 3+ years in building and launching production software; familiarity with front-end (React.js, Next.js, Angular) and back-end (Node.js, Java / Spring Boot), and REST/GraphQL, HTML/JS etc. • GenAI Mastery: experience with large language models (LLMs), diffusion models, prompt engineering, RAG pipelines, vector databases, multimodal AI (text, image, video, audio) etc. • Cloud & DevOps / Infrastructure: comfort with AWS / Azure / cloud compute, containerization (Docker, Kubernetes), serverless, CI/CD, infrastructure as code, monitoring/logging etc. • Adobe Platform Fluency: understanding of Firefly APIs/services, Creative Cloud SDK/APIs, Experience Cloud integrations are nice to have. • Strong Communication & Customer Centricity: ability to translate technical details to non-technical stakeholders and work with customers. • Ability to thrive in ambiguous / fast-changing environments ("startup DNA"). • Track record of enterprise consulting, solution architecture, or technical pre-sales. • Knowledge of responsible AI practices, including model evaluation, bias mitigation, and compliance. • • Entrepreneurial mindset with the ability to thrive in ambiguous, fast-moving environments—identifying opportunities, driving solutions end-to-end, and innovating beyond defined playbooks. • Master’s in Computer Science, AI/ML, or related field. What Success Looks Like • Customers achieve measurable outcomes (efficiency, creativity, revenue impact) from deployed AI solutions. • AI adoption is accelerated through seamless integration with customer workflows. • Strong partnerships are formed with product, research, and business leaders to continuously advance the AI platform. • You are seen by customers not just as an engineer, but as a strategic advisor driving AI transformation.