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# AI QE Test Platform Strategy & Architecture

- **Company:** LEDGENT
- **Location:** Alameda, CA, United States
- **Experience:** Experienced
- **Salary:** $291,200.0 - $346,653.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Audit Trail, Software as a Service, Software Quality, Dataspaces, Github, Machine Learning, Performance Tuning, Systems Development Life Cycle, OpenAI, Microsoft Copilot, Software Engineering, Software Systems, Feature Engineering, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Multi-Cloud, Agentic-AI, AI Platforms, Machine Learning Operations, Claude, Semantic Kernel, GXP, Katalon Studio, Databricks
- **Published:** October 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=7bf62b994187afc5

## About the Role

* 5+ years in software quality engineering and testing, AI/ML engineering
 * 3+ years hands-on experience with AI Test platforms (AWS preferred)
 * Proven experience with:

o Experience with one or more AI QE Testing Platforms: Tricentis Testim/Tosca, ACCELQ, Mabl, LambdaTest, Katalon

o Enterprise LLM platforms (e.g., Claude, OpenAI, or similar)

o Strong understanding of LLM architectures (RAG, fine-tuning, embeddings, Vector DBs, Graph DBs, Multi agent orchestration)

Preferred Qualifications

 * Familiarity with:

o GxP validation processes for AI/ML systems

 * Exposure to:

o Agent frameworks (LangChain, Semantic Kernel, etc.)

o AI testing and evaluation tooling

o Multi-cloud / hybrid architectures

Key Competencies

 * Strategic + hands-on balance (thinks like an architect, executes like an engineer)
 * Ability to translate emerging AI trends into enterprise value
 * Strong systems thinking across platforms, data, and workflows
 * Excellent stakeholder communication-able to influence senior leadership and engineering teams alike
 * Bias for action-rapid experimentation and iterative delivery

TECHNICAL SKILLS

Must Have

 * Agile
 * Agile Application Development
 * AI Test Platform
 * Amazon Web Services (AWS)
 * Anthropic Claude AI
 * Copilot
 * GitHub
 * IT software QE Testing leveraging AI test tools and test platforms
 * SDLC

## Description

* AI QE Test Platform Strategy & Architecture

o Help define and mature Exelixis' enterprise AI QE Test platform architecture across cloud and data ecosystems

o Design interoperable AI driven QE test solutions to support software solutions to support

o AWS AI stack (Bedrock, SageMaker, model hosting, orchestration)

o Databricks / Mosaic AI (ML lifecycle, feature engineering, LLM ops)

o Claude for Enterprise (secure conversational AI and enterprise workflows)

o SaaS and in-house developed software products

 * AI Capability Engineering & Operations

o Operationalize reusable AI capabilities:

§ Prompt, tool, and agent orchestration frameworks

§ Evaluation, monitoring, and observability pipelines

§ Enable secure, compliant AI usage (GxP, HIPAA where applicable)

o Implement AI platform guardrails

o Auditability and traceability

 * Design and operationalize Defect Statistics
 * Drive adoption of agentic software development lifecycle (SDLC) practices
 * Define frameworks for