Responsibilities:
Serve as the technical lead, establishing code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team.
Partner with Sales and Tech Leadership to define requirements for high-value opportunities, deploying specialized experts (e.g., MLOps, GenMedia, or Agentic systems) to key accounts.
Lead technical hiring for FDE, evaluating AI/ML expertise, systems engineering, and coding skills to build an exceptional engineering team.
Identify skill gaps in emerging tech (Model Context Protocol (MCP), tool-calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack.
Collaborate with Product and Engineering to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.
Minimum qualifications:
Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
8 years of experience in cloud computing or a technical customer-facing role.
5 years of experience managing a software engineering, FDE, or similar technical customer-facing team in a cloud computing environment.
Experience in Python or similar coding language.
Experience developing AI/GenAI solutions utilizing AI tools, or designing multi-agent workflows or Retrieval-Augmented Generation (RAG) systems.
Preferred qualifications:
Master’s degree or PhD in AI, Computer Science, or a related technical field.
Experience designing end-to-end secure, observable multi-agent systems using complex design patterns (e.g., ReAct, self-reflection), state management, and tool-calling protocols.
Experience working with manufacturing and conglomerates customers.
Experience designing intuitive interfaces for complex AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust.
Experience architecting AI solutions within complex infrastructures, ensuring data sovereignty and secure governance.
Experience performing discovery interviews to identify business problems and translate complex hardware/AI constraints for C-suites and technical teams.
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