QE Solution Director
COFORGE Marketing, Houston, TX, United States
Role : QE Solution Director
Skills : GHCP (GitHub Copilot), Azure OpenAI, AI-based test generation
Experience:
14 + Years. Location : Houston TX.
Do not pass up this chance, apply quickly if your experience and skills match what is in the following description.
Role Summary We are seeking an
AI-Driven Quality Engineering (QE) Solution Architect
to lead the design and rollout of
next‑generation, AI-enabled QE solutions
powered by platforms such as
GitHub Copilot (GHCP) , Azure OpenAI, and intelligent automation toolchains. This role will drive
RFP/proposal solutioning , lead
strategic AI pilots , and deliver
tangible quality, velocity, and cost benefits
that accelerate client adoption of AI across the account. The architect will work closely with Sales, Delivery, DevOps, and Enterprise Architecture to position differentiated, automation-first QE solutions and enable account mining. Key Responsibilities: 1. AI-Enabled QE Solutioning (Primary Charter) Architect
AI-first QE solutions
leveraging GHCP, Generative AI, ML-based defect prediction, autonomous test generation, and intelligent test data creation. Define AI use cases across the entire QE lifecycle—test design automation, risk-based optimization, impact analytics, and continuous validation. Build reusable
AI accelerators, prompts, copilots, templates , and solution kits to differentiate QE offerings. Evaluate and recommend best-fit AI/QE platforms for client ecosystems including GHCP, Azure OpenAI, Selenium, Playwright, Tricentis, Katalon, and cloud-native DevOps stacks. Establish governance for responsible AI usage in QE. 2. Strategic Projects, Pilots & Account Mining Lead
AI pilots and proof-of-value (PoV) initiatives
to demonstrate measurable impact—cycle time reduction, automation uplift, defect leakage reduction, and cost efficiency. Drive
cross-account AI adoption
by identifying areas for modernization, automation, and AI-led productivity improvements. Shape new opportunities within accounts through
strategic programs , capability showcases, and client workshops. Develop account-specific
AI roadmaps , maturity models, and transformation charters. 3. Solutioning & Pre-Sales Leadership Own QE solutioning for
RFPs, RFIs, and proposals , including estimation, delivery models, staffing, and differentiators. Create compelling value narratives highlighting
AI-enabled acceleration, automation efficiency, and quality cost reduction . Represent QE in orals, client demos, and AI capability walk-throughs. Build scalable solution blueprints that integrate functional, automation, performance, security, data, and AI-driven validation. 4. Quality Engineering Leadership Provide architectural direction across
Functional QA, UI/API automation, Performance, Security, and AI-led QE . Recommend enterprise-grade QE toolchains optimized for ERP, CRM, API-led, and cloud-native digital ecosystems. Drive QE modernization by introducing
self-healing automation, autonomous test generation, shift-left testing , and DevOps‑integrated quality gates. 5. Collaboration, Governance & Delivery Alignment Work with Delivery, DevOps, Engineering, and Enterprise Architecture to ensure
solution feasibility and adoption . Ensure seamless transition from solution to delivery including guardrails, scope clarity, and quality governance. Align solutions with organizational cost models, margin expectations, and client value realization frameworks. Required Skills & Experience 12–15 years in QE;
3+ years in QE Architecture, AI-led QE, Solutioning, or Pre-Sales . Strong expertise with
GHCP (GitHub Copilot), Azure OpenAI, AI-based test generation , and enterprise automation frameworks. Demonstrated experience leading client-facing
AI pilots/PoVs . Ability to create high-quality proposal content—estimates, assumptions, solution writeups, value metrics. Excellent communication, storytelling, and stakeholder influence skills. Experience working with bid teams and large transformation programs. Preferred Skills / Certifications Experience with AI/QE in
ERP (SAP/Oracle/NetSuite), CRM, MuleSoft/API-led integrations , and cloud modernization programs. exposure to performance engineering, application security, and DevOps pipelines. xywuqvp Certifications: ISTQB, Agile, AWS/Azure, DevOps, GitHub, or AI certifications.
14 + Years. Location : Houston TX.
Do not pass up this chance, apply quickly if your experience and skills match what is in the following description.
Role Summary We are seeking an
AI-Driven Quality Engineering (QE) Solution Architect
to lead the design and rollout of
next‑generation, AI-enabled QE solutions
powered by platforms such as
GitHub Copilot (GHCP) , Azure OpenAI, and intelligent automation toolchains. This role will drive
RFP/proposal solutioning , lead
strategic AI pilots , and deliver
tangible quality, velocity, and cost benefits
that accelerate client adoption of AI across the account. The architect will work closely with Sales, Delivery, DevOps, and Enterprise Architecture to position differentiated, automation-first QE solutions and enable account mining. Key Responsibilities: 1. AI-Enabled QE Solutioning (Primary Charter) Architect
AI-first QE solutions
leveraging GHCP, Generative AI, ML-based defect prediction, autonomous test generation, and intelligent test data creation. Define AI use cases across the entire QE lifecycle—test design automation, risk-based optimization, impact analytics, and continuous validation. Build reusable
AI accelerators, prompts, copilots, templates , and solution kits to differentiate QE offerings. Evaluate and recommend best-fit AI/QE platforms for client ecosystems including GHCP, Azure OpenAI, Selenium, Playwright, Tricentis, Katalon, and cloud-native DevOps stacks. Establish governance for responsible AI usage in QE. 2. Strategic Projects, Pilots & Account Mining Lead
AI pilots and proof-of-value (PoV) initiatives
to demonstrate measurable impact—cycle time reduction, automation uplift, defect leakage reduction, and cost efficiency. Drive
cross-account AI adoption
by identifying areas for modernization, automation, and AI-led productivity improvements. Shape new opportunities within accounts through
strategic programs , capability showcases, and client workshops. Develop account-specific
AI roadmaps , maturity models, and transformation charters. 3. Solutioning & Pre-Sales Leadership Own QE solutioning for
RFPs, RFIs, and proposals , including estimation, delivery models, staffing, and differentiators. Create compelling value narratives highlighting
AI-enabled acceleration, automation efficiency, and quality cost reduction . Represent QE in orals, client demos, and AI capability walk-throughs. Build scalable solution blueprints that integrate functional, automation, performance, security, data, and AI-driven validation. 4. Quality Engineering Leadership Provide architectural direction across
Functional QA, UI/API automation, Performance, Security, and AI-led QE . Recommend enterprise-grade QE toolchains optimized for ERP, CRM, API-led, and cloud-native digital ecosystems. Drive QE modernization by introducing
self-healing automation, autonomous test generation, shift-left testing , and DevOps‑integrated quality gates. 5. Collaboration, Governance & Delivery Alignment Work with Delivery, DevOps, Engineering, and Enterprise Architecture to ensure
solution feasibility and adoption . Ensure seamless transition from solution to delivery including guardrails, scope clarity, and quality governance. Align solutions with organizational cost models, margin expectations, and client value realization frameworks. Required Skills & Experience 12–15 years in QE;
3+ years in QE Architecture, AI-led QE, Solutioning, or Pre-Sales . Strong expertise with
GHCP (GitHub Copilot), Azure OpenAI, AI-based test generation , and enterprise automation frameworks. Demonstrated experience leading client-facing
AI pilots/PoVs . Ability to create high-quality proposal content—estimates, assumptions, solution writeups, value metrics. Excellent communication, storytelling, and stakeholder influence skills. Experience working with bid teams and large transformation programs. Preferred Skills / Certifications Experience with AI/QE in
ERP (SAP/Oracle/NetSuite), CRM, MuleSoft/API-led integrations , and cloud modernization programs. exposure to performance engineering, application security, and DevOps pipelines. xywuqvp Certifications: ISTQB, Agile, AWS/Azure, DevOps, GitHub, or AI certifications.