Responsibilities
- Architect and implement production-ready AI applications, including copilot systems, retrieval models, and agent-driven workflows
- Convert business challenges into scalable technical implementations using current AI engineering standards
- Create backend systems, APIs, and application frameworks that embed AI functionality into enterprise platforms
- Develop multi-agent architectures, autonomous agents, automated processes, and systems that support decision-making
- Operationalize AI models in production with strong emphasis on security, monitoring, observability, evaluation, and compliance
- Design AI solutions that interoperate with corporate data systems, databases, APIs, messaging infrastructure, and business software
- Work closely with cross-functional teams including engineering, data, product, architecture, security, and business units
- Demonstrate experience running containerized workloads on Kubernetes, including scaling, networking, resource allocation, and monitoring
- Develop and share reusable tools, frameworks, technical components, and insights to advance AI engineering capabilities
- Keep pace with advancements in AI technology and propose actionable strategies that enhance client results
Compensation
Not specified
Work Arrangement
US-based role
Team
Collaborative environment with engineering, data, product, and business teams
Not specified
