About CommBox
CommBox is an AI-powered omnichannel customer engagement platform serving 250+ enterprise customers across banking, telecom, healthcare, utilities, insurance, retail, and other large-scale service organizations.
Our platform powers real customer interactions across voice, WhatsApp, chat, email, and additional digital channels. CommBox AI Agents, Voice AI, automation flows, and knowledge-based assistants already handle millions of production conversations for enterprise brands.
As AI adoption accelerates, we are expanding our Forward Deployed Engineering (FDE) function — the team responsible for turning enterprise AI potential into real, working AI agents in production.
עיקרי התפקיד
We are looking for an experienced FDE Team Lead to build, lead, and grow our Forward Deployed Engineering team while remaining hands-on in high-impact enterprise AI implementations.
In this role, you will balance team management, technical leadership, and execution. You will establish implementation methodologies, scale delivery processes, mentor engineers, and ensure your team delivers robust AI agents that drive measurable enterprise business outcomes.
At CommBox, FDEs sit between Product, Engineering, Customer Success, and enterprise stakeholders. As a Team Leader, you will serve as the bridge for high-stakes projects, drive execution quality, and partner directly with leadership to scale our deployment capabilities.
Team Leadership & Management: Lead, mentor, and hire a high-performing team of Forward Deployed Engineers. Conduct code/design reviews, support professional growth, and balance capacity allocation across projects.
Execution & Delivery: Own overall delivery timelines and quality for enterprise deployments. Ensure agents achieve target operational metrics (deflection, containment, latency, CSAT).
Methodology & Playbooks: Build, standardize, and scale CommBox’s AI agent implementation methodology, RAG architectures, prompt frameworks, evaluation tools, and deployment templates.
Hands-on Implementation: Lead by example on flagship accounts — designing agent behavior, workflows, MCP/API integrations, and complex business logic.
Enterprise Discovery & Design: Facilitate technical workshops with customer executives and architecture teams to define automation strategies and solution boundaries.
Product Feedback Loop: Work closely with Product and Engineering to turn custom field solutions into core platform features and reusable enterprise connectors.
Quality & Observability: Establish quality assurance benchmarks across the team, including hallucination checks, test-set evaluation pipelines, and conversation analytics.
What We’re Looking For
Leadership Experience: 2+ years of experience leading a technical team (FDE, Solutions Engineering, Professional Services, Implementation, or Tech Lead background).
Hands-on AI Expertise: Deep understanding of LLMs, agentic workflows, prompt design, tool usage, RAG architectures, guardrails, and AI failure modes.
System Integration: Solid experience working with APIs, MCPs, webhooks, and enterprise integration patterns.
Enterprise Delivery Track Record: Proven experience managing technical delivery, scope, and execution for large enterprise clients.
Strong Customer Presence: Excellent executive-facing communication skills — able to navigate ambiguity, realign expectations, and explain complex AI architectures simply.
Technical Education: Computer Science degree or equivalent technical academic background.
Languages: Fluent Hebrew and professional English (spoken and written).
Strong Advantages
Hands-on development experience in TypeScript, Node.js, Python, or C#.
Experience with Voice AI, CCaaS platforms, WebRTC, or contact center automation.
Expertise in AI evaluation, observability platforms, and automated test frameworks.
Prior experience in high-growth startups or scaling global delivery teams.
What Makes You Successful in This Role
You combine technical depth with strong people leadership and operational execution. You know how to elevate the engineers around you, turn repeated manual work into scalable playbooks, and step in directly when complex technical challenges arise. You thrive on connecting business objectives to enterprise AI capabilities.