Divisional AI Engineer III
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Open
KeyrusCloud is a consulting firm focused on helping organizations become more data-driven. Its work combines digital transformation with technology solutions for businesses, drawing on experience across multiple countries and continents. The company describes its approach as collaborative and innovative, with an emphasis on quality delivery, social responsibility, and a workplace where teams can grow their skills and work with new technologies.
Forward Deployed AI Engineer
Deploy production AI solutions for Keyrus, an enterprise intelligence consultancy. Connect APIs, cloud platforms, enterprise systems, and client workflows.
United States
New York$135,000 – $155,000 / year
RemoteFull-timeMiddleSeniorEnglish RequiredAI EngineerMachine Learning EngineerDescription
- Lead client discovery to map systems, data, workflows, and integration needs.
- Turn business requirements and approved architectures into actionable implementation plans.
- Build production solutions that connect APIs, enterprise applications, cloud and data platforms, and AI technologies.
- Partner with AI Engineers, Architects, and Data Engineers to solve technical challenges and deliver integrated systems.
- Manage technical deployment and rollout within the agreed scope, supporting reliable production operation.
- Help client teams troubleshoot issues, adopt solutions, and improve implementations.
- Track performance, costs, and business outcomes, and document reusable engineering practices.
- Convert successful projects into reusable Keyrus assets, such as integration patterns, deployment practices, technical documentation, and guidance for future engagements.
Requirements
- At least five years of professional experience in software or cloud engineering, enterprise integration, or related technical delivery.
- Practical experience developing, integrating, and deploying production software or AI-enabled solutions.
- Experience building and maintaining backend services, APIs, and enterprise integrations.
- Experience with cloud platforms, deployment processes, and production environments.
- Ability to turn business requirements into technical implementation plans.
- Strong client-facing consulting skills, including explaining technical decisions and working with business stakeholders.
- Proficiency in Python, TypeScript or JavaScript, Java, C#, or a similar programming language.
- Experience with REST APIs, backend services, authentication, and enterprise integrations.
- Hands-on experience with AWS, Azure, or Google Cloud.
- Knowledge of Git, CI/CD, testing, containers, and production monitoring.
- Familiarity with LLM APIs, retrieval-augmented generation (RAG), AI agents, and generative AI application integration.
- Understanding of application security, system reliability, and cloud deployment practices.
- Production generative AI application or agentic workflow development experience is a plus.
- Familiarity with LangGraph, MCP, OpenAI, Anthropic, or similar technologies is a plus.
- Experience with Kubernetes, Docker, or infrastructure as code is a plus.
- A background in backend, full-stack, data, or cloud engineering is a plus.
- Experience delivering solutions in regulated or complex enterprise settings is a plus.
- Consulting, professional services, or client-embedded engineering experience is a plus.
Benefits
- Health insurance for employees and their families.
- 401(k) plan.
- Monthly wellness allowance.
- Four weeks of paid vacation.
- French and English language courses.
- Continuing education opportunities, including in-house learning, conferences, events, courses, and certifications.
- Regular social events, including happy hours and trivia nights.
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