Agentic AI Forward Deployment Engineering Lead

Netomi•Toronto, ON

15h

About The Position

As an Agentic AI Forward Deployment Engineering Lead at Netomi, you will serve as the primary technical and delivery leader responsible for transforming enterprise customer requirements into production-grade Agentic AI solutions. You will partner directly with customers to understand their business processes, design scalable AI-powered workflows, lead end-to-end implementations, and ensure successful deployments that deliver measurable business outcomes. This role sits at the intersection of Solution Architecture, Product, Delivery Management, and AI Engineering. You will own the complete customer deployment lifecycle—from discovery and solution design to implementation, quality assurance, go-live, and continuous optimization. You will work closely with Customer Success, Product, Engineering, Integration Engineers, and QA teams while acting as a trusted advisor to enterprise stakeholders throughout their AI transformation journey.

Requirements

6–12 years of experience in Solution Architecture, Enterprise Delivery, Implementation Consulting, Professional Services, or Technical Program Management for SaaS or AI platforms.
Proven experience leading complex enterprise software deployments and customer implementations.
Strong ability to gather business requirements and translate them into scalable technical solutions.
Experience managing cross-functional delivery teams across engineering, product, QA, and customer-facing functions.
Deep understanding of APIs, enterprise integrations, system architecture, data flows, and distributed systems.
Excellent customer-facing communication, stakeholder management, and executive presentation skills.
Strong project leadership and problem-solving capabilities with a focus on execution excellence.

Nice To Haves

Experience with Conversational AI, Agentic AI, LLM-based systems, RPA, workflow automation, or customer service platforms.
Background in enterprise customer experience, contact center technologies, CRM, or ticketing platforms.
Experience working with large enterprises in airlines, BFSI, telecom, hospitality, retail, or healthcare industries.
Familiarity with AI evaluation frameworks, prompt engineering, workflow orchestration, and autonomous agent systems.
Experience scaling deployment methodologies and leading global enterprise implementations.

Responsibilities

Lead workshops and discovery sessions with enterprise customers to understand business processes, operational workflows, KPIs, customer journeys, and automation opportunities.
Translate customer requirements into scalable Agentic AI architectures and implementation strategies.
Design end-to-end AI agent workflows including intents, reasoning flows, tool usage, integrations, escalation paths, guardrails, and governance controls.
Create comprehensive solution blueprints, functional specifications, and implementation plans.
Identify risks, dependencies, and technical constraints early in the engagement lifecycle.
Own the end-to-end delivery of customer deployments from kickoff through production launch.
Act as the technical delivery lead coordinating activities across Product, Engineering, Integration, QA, and Customer Success teams.
Drive project execution, milestone tracking, issue resolution, and stakeholder communication.
Ensure deployments are delivered on schedule with high quality and minimal rework.
Provide hands-on guidance during complex implementations and critical customer engagements.
Define integration strategies across enterprise systems including CRMs, ticketing platforms, customer data platforms, APIs, internal tools, and third-party applications.
Collaborate with customer engineering teams to validate technical feasibility and implementation approaches.
Review integration designs, data flows, security requirements, authentication models, and operational readiness plans.
Support implementation teams in troubleshooting and resolving complex technical challenges.
Own deployment quality and customer acceptance criteria.
Partner with QA teams to define comprehensive test plans, validation scenarios, and success metrics.
Conduct end-to-end workflow validation, agent behavior reviews, and production readiness assessments.
Establish best practices for reliability, observability, governance, and performance monitoring.
Ensure solutions meet enterprise standards for security, compliance, scalability, and auditability.
Serve as the trusted technical advisor for customer stakeholders across CX, Operations, Product, Digital Transformation, and Engineering teams.
Present architectural recommendations, implementation roadmaps, and optimization opportunities.
Guide customers on Agentic AI best practices, governance frameworks, and operating models.
Drive executive-level discussions around automation strategy, ROI, and adoption.
Develop reusable deployment playbooks, implementation frameworks, and solution templates.
Capture lessons learned and establish best practices across customer deployments.
Collaborate with Product and Engineering teams to influence platform enhancements based on customer feedback and implementation experience.
Stay current with advancements in Agentic AI, LLMs, workflow orchestration, and enterprise automation technologies.