Forward Deployment Engineering Leader

The Glove; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

The Glove Company is seeking an FDE Leader to anchor onshore technical and people leadership for Agentic AI initiatives across customer-facing digital platforms. This senior, hands-on role blends architecture, coding, and team mentorship to deliver scalable, production-ready solutions.

You will build a high-performing team of Forward Deployment Engineers, govern multi-agent architectures, and own end-to-end delivery on strategic engagements.

Qualifications

• 15–20+ years in enterprise architecture or technical delivery.
• 5+ years leading high-performing technical teams.
• Strong API-first design and distributed systems experience.
• Hands-on coding and architecture review capability with Python.

Responsibilities

• Lead and scale a team of Forward Deployment Engineers.
• Design end-to-end agentic architecture for digital experiences.
• Oversee multi-agent orchestration patterns and MCP standards.
• Own end-to-end delivery outcomes on strategic engagements.
• Translate agentic AI concepts into business value for executives.

Skills

Python proficiency

Architecture leadership

API-first design

Code reviews

Tools

LangGraph

LangChain

Semantic Kernel

LangSmith

Langfuse

Job description

FDE Leader – Forward Deployment Engineering Leader North America

Agentic AI & Digital Platforms

Role Overview

A senior hands-on techno-functional leadership role — not pure research and not purely strategic. The FDE Leader serves as the onshore technical and people-leadership anchor for Agentic AI initiatives across customer-facing digital platforms.

You will build, lead, and scale a high-performing team of Forward Deployment Engineers (FDEs), translate business intent into scalable, governed, production-ready agentic systems, and hold the architectural and delivery line across multiple concurrent client engagements.

The right person still codes, reviews architecture, and debates hard trade-offs in the same week they coach their team, brief a VP, and shape engagement strategy. This is a player-coach role with clear ownership of both team outcomes and client value.

Key Responsibilities

Team Leadership & Capability Building

• Hire, develop, coach, and retain a high-performing team of Forward Deployment Engineers (onshore and offshore).
• Set the technical bar, performance standards, career pathways, and culture of excellence for the FDE practice.
• Lead across onshore/offshore delivery models; manage capacity, utilization, and engagement staffing.
• Mentor senior FDEs and architects; conduct regular code/architecture reviews and technical coaching.
• Build repeatable playbooks, reference architectures, reusable assets, and delivery standards that scale beyond individual engagements.

Agentic Architecture & Delivery Ownership

• Design and govern end-to-end agentic architecture for digital experiences spanning apps, loyalty, payments, and commerce workflows.
• Architect and oversee multi-agent orchestration patterns — orchestrator/sub agent hierarchies, tool/function calling, stateful graph-based workflows, and agent memory (short-term, session, long-term).
• Establish and enforce MCP (Model Context Protocol) standards for governed tool and enterprise service exposure.
• Define and implement runtime guardrails: spend controls, fraud detection hooks, human-in-the-loop checkpoints, and full auditability trails.
• Lead AI agent integration with retail systems — catalog, inventory, pricing, promotions, loyalty, and checkout.
• Set and operationalize LLMOps standards across the team: prompt versioning, RAG pipeline governance, evaluation harnesses, and observability (latency, token cost, drift, safety).

Client & Stakeholder Leadership

• Serve as the primary technical and delivery interface between business leaders, delivery teams, platform partners, and Mastech leadership.
• Own end-to-end delivery outcomes on strategic engagements — from discovery and architecture through production deployment and measurable value realization.
• Translate complex agentic AI concepts into clear business-value language at the executive level.
• Make architectural trade-off calls under pressure and defend them with data and judgment.

Required Qualifications

Foundational & Leadership

• 15–20+ years in enterprise/platform architecture, solutions engineering, or technical delivery; 5+ years leading high-performing technical teams (preferably Forward Deployed, Solutions, or customer-facing engineering teams).
• Proven experience hiring, coaching, and scaling teams of engineers in onshore/offshore or matrixed models.
• Strong command of API-first design, distributed systems, event-driven architecture, and real-time data platforms.
• Hands-on enough to write reference implementations and lead rigorous code reviews — strong Python proficiency required.

Agentic AI – Core Requirement

• Production experience shipping LLM-based agent systems (not just prototypes or PoCs).
• Hands-on depth with agent frameworks (LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or equivalents) and clear judgment on when to use which patterns.
• Working knowledge of ReAct/plan-execute patterns, multi-agent handoffs, advanced RAG (chunking, hybrid retrieval, reranking), context/prompt engineering, and MCP.
• Familiarity with agent failure modes (hallucination, tool misuse, cost runaway, infinite loops) and proven approaches to architect against them.
• LLMOps experience: evaluation frameworks, observability tooling (LangSmith, Langfuse, or equivalent), and prompt/model lifecycle management.

Retail / Consumer Domain

• Meaningful exposure to retail commerce systems: catalog, pricing, promotions, loyalty, checkout, or payments. Direct retail experience strongly preferred; adjacent large-scale commerce or digital platform background considered.

Data & Integration

Comfortable with event-driven architectures (Kafka or equivalent) and the realities of enterprise data quality.

Familiarity with semantic models or knowledge graphs as agent grounding layers is a plus.

Leadership Profile

Translates agentic AI concepts into credible business-value language at the executive level.

Sets clear architectural and delivery boundaries, makes hard trade-off calls, and defends them under pressure.

Experienced leading across onshore/offshore delivery models and multi-team programs.

Comfortable operating in a fast-moving technology space with evolving standards and high client expectations.

Combines deep technical credibility with strong people leadership and commercial awareness.