Job Description:
• Lead the design and development of smart agent platforms, including how agents are created, orchestrated, and deployed.
• Define and implement systems for agent skill creation, composition, and lifecycle management.
• Build and evolve low-level agent infrastructure, including planning, reasoning, memory, and tool-use capabilities.
• Architect frameworks for embedding models into applications and enabling agents to interact with business logic and product workflows.
• Guide the development of agentic workflows that execute multi-step tasks aligned to product and business goals.
• Manage and mentor a team of engineers while contributing directly to critical system design and implementation.
• Collaborate with product and data teams to translate product requirements into agent capabilities and skills.
• Establish best practices for agent reliability, observability, evaluation, and performance optimization.
• Drive the development of systems for agent evaluation, feedback loops, and continuous skill improvement.
• Ensure scalability and robustness of infrastructure supporting multi-agent systems and distributed execution.
• Contribute to CI/CD and development workflows supporting agent deployment, iteration, and lifecycle management.
• Troubleshoot complex issues across agent behavior, orchestration systems, and underlying ML infrastructure.
• Partner with senior leadership to shape agentic platform strategy and roadmap.
Requirements:
• Extensive experience building production-grade agentic systems or AI platforms with autonomous capabilities.
• Strong hands-on expertise in low-level agent design, including planning, memory, tool use, and reasoning systems.
• Proven experience building systems for agent skill development, orchestration, and execution.
• Experience embedding machine learning models into real-world applications and product workflows.
• Strong programming skills (Python or similar) with experience building scalable backend systems for AI applications.
• Deep understanding of distributed systems, APIs, and real-time execution environments for agents.
• Experience designing and operating systems on cloud platforms such as AWS, Azure, or GCP.
• Experience managing and mentoring engineers while remaining deeply hands-on in system design and development.
• Strong debugging and problem-solving skills across complex agentic and ML systems.
• Ability to translate product goals into technical systems and agent capabilities.
• Strong communication skills and ability to collaborate across engineering, product, and data teams.
Benefits:
• Remote work options