Role overview
AI Engineer
About the Role
We are seeking a highly skilled
AI 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.
What we're looking for
- 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 .