AI Delivery Manager

AI Delivery Manager — DotKonnekt About the role DotKonnekt is hiring a AI Delivery Manager to own enterprise AI delivery end-to-end — from solution architecture through go-live — for clients deploying production-grade AI systems (conversational AI, RAG, and agentic applications) into their business operations. This is not a strategy or advisory role. You will personally architect solutions, plan and run delivery, lead the engineering team, and present to client executives. If you cannot do all four of those today, this role is not a fit. What you'll own Solution design Architect AI applications (RAG, agentic workflows, LLM orchestration) that integrate with enterprise systems ,scale to 500K monthly active users with low-latency responses, and meet enterprise security, data governance, and compliance requirements on AWS or GCP. Delivery leadership Build and run delivery plans across discovery, MVP, and production rollout — including scope sequencing, go-live criteria, team structure, timelines, and risk/dependency management. Engineering management Structure and lead the engineering team: onboarding, engineering standards, CI/CD and environment strategy, testing strategy, and operational readiness (on-call, monitoring, incident response). Executive communication Present recommended solutions and tradeoffs directly to client executives (CTO/VP/Director level) with clarity and confidence, and defend your decisions under pushback. You must have 8 years in enterprise software/AI delivery, including at least 3 years architecting and shipping production AI/ML or LLM-based systems (not pilots or POCs). Direct, hands-on experience designing systems that integrate with third-party SaaS platforms (CRM, e-commerce, support/ticketing) via APIs. Experience architecting for scale (100K concurrent/monthly active users) and for enterprise security/compliance (SOC2, data governance, PII handling). 3 years directly managing engineering teams (hiring, performance, technical mentorship) — not just "worked with engineers." Track record presenting technical solutions and tradeoffs to C-level or VP-level client stakeholders, and owning the outcome of that conversation. Working fluency in AWS or GCP AI/ML services, CI/CD practices, and modern testing/deployment strategy. Nice to have Experience in retail/e-commerce AI use cases (product discovery, customer support automation). Prior role explicitly titled Delivery Head, Head of Engineering, or Principal Solutions Architect at a consultancy or AI vendor.