Jobs at Xplor Technologies

Leads AI/ML research and development, owning enterprise evaluation methodology, predictive and decision models, experimentation, causal inference, model economics, and production deployment. Builds evaluation suites and models hands-on, monitors performance and cost, prototypes agentic techniques, and guides AI-native engineering practices. The role also develops a small team, raises organizational ML fluency, supports data-as-a-service benchmarks, and communicates model uncertainty and business value to executives.

Leads Product Operations for AI initiatives across productivity, customer adoption, commercialization, governance, measurement, and cost visibility. Builds executive scorecards, establishes portfolio decision rights, tracks AI value and risks, standardizes product and delivery metrics, supports launch readiness, manages vendor oversight, and develops a product operations team. Partners with Finance, Product, Engineering, GTM, Security, Legal, Privacy, and executive leaders to connect AI investments with revenue, margin, adoption, retention, and operational outcomes.

Lead product strategy for AI-driven business automation and a monetized data-as-a-service offering. Build enterprise AI governance, agent operating models, evaluation standards, privacy controls, and responsible AI practices. Develop an AI champion network, prioritize automation opportunities, and measure productivity gains. Define data products, customer segments, pricing, packaging, and go-to-market plans while partnering across engineering, security, legal, privacy, risk, and business units.

Own reliability and operations for a multi-tenant AI agent platform running on AWS. Define SLOs, observability, alerting, disaster recovery, model-provider resilience, tenant isolation, security guardrails, safe deployments, and cost controls. Manage infrastructure through Terraform and Spacelift, lead incident response and game days, improve PostgreSQL resilience, and establish standard deployment practices for product teams. Partner with Security and Privacy on AI risk controls and regional data residency.

Designs and develops backend platform software for a multi-tenant SaaS environment using Python, Django, Ember, and PostgreSQL. Responsibilities include building testable systems, leading technical design initiatives, troubleshooting defects, collaborating remotely, reviewing code through pull requests, and contributing to team processes. The role also involves AWS-based development, Docker, APIs, SQL, background jobs, CI/CD, authentication, observability, and production debugging.