Lead technical onboarding, environment readiness (capacity, quotas, security, IAM/SSO, enterprise connectors, ECMs, and data residency), and organizational change management required to operationalize AI-driven workflows into daily production.
Embedded with customer engineering and business teams to map workflows and data pipelines, identify integration constraints, shape tools/APIs, and define MVP requirements for GenAI and autonomous agent systems.
Define impact hypotheses, baseline benchmarks, and measurable KPIs, tracking production consumption velocity, deliverable reliability, and business ROI to report outcomes to C-suite and executive sponsors.
Structure and own end-to-end delivery roadmaps for multi-workstream AI deployments, defining milestones, technical dependencies, acceptance criteria, and sequencing decisions to protect the critical path while leading technical delivery across engineers.
Minimum qualifications
Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
5 years of experience in customer-facing technical delivery leadership, technical engagement management, solutions architecture, or enterprise AI/Cloud consulting.
Experience reading, evaluating, or debugging code in a general-purpose coding language (e.g., Python, Java, JavaScript) and diagnosing architectural blockers.
Experience in system design or orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI).
Experience structuring technical delivery roadmaps, managing production deployments, and interfacing with product or engineering organizations.
Ability to communicate in English and Spanish fluently to engage with regional enterprise customers and global product teams.
Preferred qualifications
Experience leading enterprise Generative AI, LLM-based agentic workflows, or RAG architecture engagements from prototype to production readiness.
Experience working closely alongside Forward Deployed Engineers (FDEs), software engineering squads, sales and Product/Research teams to build and scale custom technical solutions.
Sharp sequencing instincts with the ability to move fluidly between system-level architecture discussions and execution-level technical detail (e.g., code review, API integrations, evaluation benchmarking).
Proven track record of operating with high autonomy in ambiguous environments, establishing structure, building reusable delivery playbooks, and driving 0→1 initiatives to scale.
Bachelor’s degree in Computer Science, Engineering, a related technical field, or equivalent practical experience.
5 years of experience in customer-facing technical delivery leadership, technical engagement management, solutions architecture, or enterprise AI/Cloud consulting.
Experience reading, evaluating, or debugging code in a general-purpose coding language (e.g., Python, Java, JavaScript) and diagnosing architectural blockers.
Experience in system design or orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI).
Experience structuring technical delivery roadmaps, managing production deployments, and interfacing with product or engineering organizations.
Ability to communicate in English and Spanish fluently to engage with regional enterprise customers and global product teams.
