Head of AI Delivery

About the role
DotKonnekt is hiring a Head of AI Delivery 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 or any other client’s cloud.
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 with clarity and confidence.

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.

Core skills & tools
Solution architecture & design thinking for enterprise AI systems
Agentic AI: multi-agent orchestration, agent-to-agent protocols, tool/function calling, Model Context Protocol (MCP), LangChain/LangGraph or equivalent frameworks
RAG pipeline design, vector databases, prompt engineering, LLMOps
Claude (Anthropic) and other frontier LLM APIs — hands-on build experience, not just usage
Backend/API development — FastAPI (or equivalent) for AI service layers
Cloud platforms — AWS and/or GCP (AI/ML services, deployment, scaling)
CI/CD, environment strategy, testing and release practices
Technical leadership — team structuring, mentorship, standards-setting
End-to-end project/program delivery — discovery through production rollout

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.