Artificial Intelligence Engineer

Location - Remote with occasional travel to Austin, TX / Fort Mill, SC ( Hybrid) Key Responsibilities· Define and maintain the end-to-end AI-PDLC workflow linking code-graph analysis, LLM evaluation, dispositioning, data migration, and productionization.Review outputs across the pod to ensure consistency, traceability, and coherence between iterations — recognizing that discovery continues through implementation, testing, cutover, and post-go-live defect remediation.Resolve cross-workstream conflicts (e.g., a graph finding that changes a data migration disposition) and ensure a single source of truth.Set the quality bar for what constitutes a "defensible" disposition and hold the pod accountable to it.Coordinate access to Wipro’s broader Agentic AI CoE, Data Engineering, and Architecture Community so the pod benefits from cross-engagement patterns, not just its own five members.Required Skills· Amazon Bedrock (mandatory — production experience, not POC/evaluation)AI-PDLC / AI product development lifecycle disciplineCross-workstream technical coordination across AI, data, and application teamsClient-facing communication and escalation management with senior stakeholdersArchitecture governance in regulated/financial services environmentsRelevant Experience· 10+ years in AI/data/software architecture with recent experience leading GenAI or Agentic AI delivery pods.Confirmed hands-on AWS Bedrock production deployment (not just AWS familiarity).Proven experience as a single technical point of contact for enterprise clients on complex, multi-year modernization/migration programs.Financial services / capital markets / wealth management domain experience strongly preferred.Expected Deliverables / Work Products· AI-PDLC workflow and governance modelPod status and escalation reportingCross-workstream consistency reviewsDisposition quality/defensibility bar and audit trail