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Enterprise Architect

NLB Services
Malvern, PA Contractor
POSTED ON 4/20/2026 CLOSED ON 4/22/2026

What are the responsibilities and job description for the Enterprise Architect position at NLB Services?

Role Summary

client Advice and Wealth Management Technology organization is establishing a centralized capability to accelerate the effective adoption of AI-assisted software development. This role will build and lead an AI Enablement & Coaching function that improves engineering productivity, delivery flow, and quality across the SDLC. The role blends AI coaching, delivery management, and SDLC optimization and is not tied to a specific technology stack.

Key Objectives

• Enable engineering teams to adopt AI tools responsibly and effectively

• Improve SDLC flow, cycle time, and quality using AI-assisted practices

• Establish a repeatable AI coaching and adoption model

• Introduce AI agents and accelerators to streamline delivery

• Bridge engineering, product, and leadership to drive measurable value

Core Responsibilities – AI Enablement & Coaching

Act as an AI coach for development teams; guide adoption of AI-assisted coding, testing, documentation, and review; develop best practices, guardrails, and enablement materials; run workshops and hands-on coaching sessions.

Core Responsibilities – SDLC Optimization

Assess workflows to identify bottlenecks; introduce AI-supported improvements across planning, development, testing, and CI/CD; partner with delivery leaders to improve throughput and predictability; focus on value-driven AI adoption.

Core Responsibilities – Agentic AI champion

Evaluate and pilot AI agents for testing, documentation, and workflow automation; define where agent-based automation adds value without increasing risk; collaborate with architecture and platform teams.

Delivery & Change Enablement

Ensure AI adoption aligns with delivery commitments and risk posture; track adoption and value metrics; support organizational and behavioral change.

Required Qualifications

Strong SDLC experience; exposure to AI-assisted development; experience coaching engineering teams; understanding of Agile delivery models; ability to work across multiple tech stacks.

Preferred Qualifications

Experience in financial services or regulated environments; background in engineering enablement or developer productivity; experience defining flow and productivity metrics. 10 years experience and good communication and ability to work with multiple stakeholders

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