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Senior QA Engineer responsible for designing and executing test strategies for Amazon Connect contact centers, building manual and automated Playwright/Cypress/Selenium suites across UI, API and serverless backends, validating migrations and production readiness, running UAT, incident triage, and mentoring junior QA engineers.

Lead architecture and delivery of AI-native contact center solutions using Amazon Connect and generative AI. Design AI agents, contact flows, serverless backends, analytics lakes, IaC, CI/CD, observability, and migration plans. Mentor engineers, drive technical decisions, manage risk, and support pre-sales and customer enablement.

Lead client-facing change strategy and adoption for technology and organizational transformations. Design and execute change programs, define adoption metrics, monitor readiness and risks, and apply AI-enabled approaches to improve productivity and outcomes. Build stakeholder alignment, facilitate workshops, support proposals, and drive measurable behavior change across complex organizations.

Lead AI engagements, shaping strategy and architecture. Engage with various stakeholders, design AI operating models, and facilitate workshops. Drive expansion opportunities and contribute to internal frameworks.

Lead the product workstream in client AI engagements: assess product teams, design future-state PDLC, coach PMs on AI-native workflows, scope prototypes, write executable specs and Sprint Charters, design PM training, and feed field insights into agent tooling and methodology improvements.

Partner with sales and enterprise clients to design, architect, and evangelize Amazon Connect-based contact center and CX solutions. Lead pre-sales discovery, proposals, POCs, and workshops; integrate AI/ML (Amazon Lex, Bedrock, generative AI); produce architectures aligned with AWS Well-Architected practices and regulatory/security requirements for industries like healthcare and finance.

As a Principal Strategist, you will guide financial services clients in their cloud transformation journeys by developing actionable plans, enhancing adaptability, and driving growth of strategic accounts.

The AI/ML Engineering Manager leads a team of ML engineers and architects, managing hiring, performance, and customer engagements while providing technical guidance in ML operations and architecture.

The role involves leading ML client engagements, shaping strategies, advising on ML architecture, and influencing project outcomes, while guiding teams and driving business value.

The Principal Cloud Architect will lead cloud solution designs and implementations for clients, guiding teams, mentoring staff, and driving innovation in AWS architectural strategy.