Top Tech Jobs & Startup Jobs

Lead and develop the Procure-to-Pay solution engineering and business development team to design tailored client solutions, drive demos, RFP/RFI responses, pricing and proposals, manage pipeline and partnerships, inform portfolio strategy, represent solutions externally, and lead responsible AI adoption across the function to grow market presence and client value.

Design and build scalable backend systems and cloud infrastructure for AI/ML applications, while implementing engineering standards and mentoring engineers.

The internship supports the Indirect Spend team through supplier engagement, data analysis, and project execution, requiring interaction with various teams and leadership.

Manage day-to-day engineering delivery for AI Intelligent Automation initiatives, leading one or more Delivery PODs through the AI Delivery Lifecycle. Oversee Agile execution, Azure DevOps planning, sprint management, release readiness, production support coordination, delivery reporting, KPI tracking, risk mitigation, and continuous improvement to ensure predictable, high-quality delivery of enterprise automation solutions.

Leads commercial IT strategy, capability ownership, product owner teams, governance, roadmap prioritization, investment planning, and cross-domain initiatives. Builds executive and business partnerships, aligns technology roadmaps with enterprise value, and ensures platform health, delivery readiness, adoption, and sustainability. Oversees CRM, sales enablement, pricing, customer service, marketing automation, community platforms, and related digital commercial capabilities.

Develop automated analytics products and advanced data science solutions using machine learning, NLP, statistical modeling, predictive analytics, and generative AI. Lead end-to-end workflows from data preparation and experimentation through model validation, deployment, and visualization. Partner with product, engineering, and platform teams to move solutions from research into production, communicate findings to technical and non-technical audiences, and guide other data scientists.

Lead strategy, architecture, and execution of enterprise IAM platforms for SaaS products. Define multi-year roadmaps, modernize authorization (ReBAC/ABAC/Policy-as-Code), support human and non-human identities, oversee architecture and operations, mentor engineering leaders, drive AI-enabled engineering practices, and align IAM capabilities with security and business priorities.

Develop and deploy scalable data science products using machine learning, generative AI, NLP, statistical modeling, and predictive analytics. Analyze complex datasets, manage end-to-end modeling workflows, communicate insights through dashboards and presentations, and partner with engineering teams on production deployment. Provide technical guidance, apply responsible AI and model governance practices, and evaluate emerging technologies for business and clinical outcomes.

Leads the design, development, and deployment of advanced data science, machine learning, generative AI, and agentic AI solutions. Builds scalable analytics products, RAG systems, and evaluation frameworks; establishes technical standards and responsible AI governance; mentors data scientists; and partners with engineering teams to deploy and monitor production solutions. Translates complex analyses into actionable clinical, operational, and economic insights while guiding technical strategy and client-focused initiatives.

Lead architecture and development of scalable, secure systems; set engineering standards and CI/CD practices; mentor engineers; drive SRE/DevOps collaboration; adopt AI/ML tools; own incident response, root-cause analysis, performance optimization, IaC and cloud-native improvements; align technical roadmaps with product and business goals.