Serve as the technical lead, establishing code standards, architectural standard procedures, and benchmarks to elevate engineering excellence across the team.
Partner with Sales and Tech Leadership to define requirements for opportunities, deploying experts (MLOps, GenMedia, or Agentic systems) to key accounts.
Lead technical hiring for the Field Solutions Architect team, evaluating AI/ML expertise, systems engineering, and coding skills to build the engineering squad.
Identify skill gaps in emerging tech (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 road maps while building internal tools to drive organizational efficiency.
Minimum qualifications:
Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
7 years of experience in cloud computing or a technical customer-facing role, with experience using Python.
2 years of experience managing a software engineering team, Field Solutions Architect team, or a similar technical customer-facing team in a cloud computing environment.
Experience developing AI or Generative AI solutions utilizing AI Tools and designing multi-agent workflows and Retrieval-augmented generation (RAG) systems.
Preferred qualifications:
Master's degree or PhD in Computer Science, AI, Machine Learning, or a related technical field.
Experience in designing interfaces for AI and agentic systems.
Experience in architecting AI solutions within infrastructures, ensuring data sovereignty and secure governance.
Ability to design observable multi-agent systems using design patterns (ReAct, self-reflection,etc), state management, and tool-calling protocols.
Ability to perform ‘discovery' interviews to find the business problem and translate hardware/AI constraints for C-suites and technical teams.
