AI Software​/Platform Engineering - OpenShift​/Observability

Please find details for this position below:

Title:

AI Software/Platform Engineering - Open Shift/Observability

Location:

IRVING, TX & CHARLOTTE, NC – Hybrid Roles

Duration: 12 months, convert to hire - H1B or C2C, only W2

• Client is seeking a hands-on, forward-thinking Specialty Software Engineer to help build and scale a high-impact Research & Innovation Engineering practice focused on identifying, evaluating, and recommending emerging technologies—turning opportunities into measurable enterprise value. This is a unique opportunity to shape the technical foundation of an innovation pipeline that accelerates enterprise transformation through evidence-based adoption and investment decisions.
• In this role, you will drive structured, secure, and automated technology evaluations by leveraging an existing PoC Lab platform to enable rapid, parallel, and isolated testing of emerging solutions. You will partner with vendors and platform teams to provision and tailor use-case–specific environments, maximizing reuse while minimizing friction.
• You will define and operationalize standardized evaluation frameworks—including test patterns, success criteria, artifact models, scoring rubrics, and reporting structures—and build automated assessment pipelines that deliver consistent, objective, and decision-grade outcomes. Leveraging modern AI/agent-based approaches, you will accelerate testing, scoring, and insight generation, bringing speed, rigor, and repeatability to every evaluation.
• You will play a pivotal role in advancing Client’s technology capabilities by rigorously validating vendor solutions and translating results into defensible, data-driven insights that shape high-impact adoption and investment decisions—unlocking commercial value through improved efficiency, reduced costs, and faster time-to-value.
• Given the increasing shift toward AI-enabled technologies, this role is ideal for an engineer who thrives in fast-paced, ambiguous environments and brings deep expertise in AI, cloud-native engineering, and automation.

• Design and operationalize standardized, reusable evaluation frameworks—including test patterns, success criteria, scoring rubrics, and artifact/reporting models—to ensure consistent, repeatable, and decision-grade outcomes.
• Lead end-to-end PoC execution by leveraging the existing PoC Lab platforms, partnering with vendors and lab teams to rapidly provision and tailor use-case–specific environments with minimal friction and maximum reuse.
• Build and apply AI-enabled automated assessment pipelines (test orchestration, data collection, validation, scoring, and results synthesis) to drive speed, accuracy, objectivity, and scalability of evaluations.
• Leverage AI/ML and agent-based approaches to streamline the full evaluation lifecycle—including intake, product scouting, market analysis, test execution, intelligent scoring, anomaly detection, and insight generation.
• Ensure all evaluations adhere to enterprise security, compliance, and auditability standards, aligned with Architecture, Info Sec, and Risk requirements.
• Develop structured, evidence-based PoV outputs and executive-ready recommendations grounded in comparative scoring and measurable outcomes.
• Maintain a centralized, reusable repository of evaluation patterns, artifacts, configurations, and outcomes to enable benchmarking, knowledge reuse, and continuous improvement.
• Provide technical leadership in vendor assessments and executive reviews, ensuring transparency, rigor, and alignment to strategic and commercial objectives.
• Drive automation of intake, triage, and prioritization to scale evaluations efficiently.
• Lead and mentor engineers, reinforcing a culture of standardization, automation, and measurable impact.

• 5+ years of software/platform engineering experience, including hands-on delivery of at least one production-grade Agentic AI solution (preferred).
• 4+ years of experience leading end-to-end PoC evaluations in collaboration with third-party lab/platform teams and vendors, including defining scope, success criteria, standardized test patterns, execution plans, and scoring…