Top AI & Machine Learning Jobs

Support AI risk intake, assessments, classification, mitigation tracking, approval evidence, policy alignment, AI inventory quality, governance reporting, escalations, and audit readiness. Coordinate with security, privacy, legal, architecture, and business stakeholders. Evaluate information security and privacy risks, including confidentiality, integrity, availability, data storage, processing, transmission, and lifecycle protection. Apply AI governance, model risk management, responsible AI, NIST AI RMF, ISO/IEC 42001, GDPR, and CCPA requirements.

Build and support AI-enabled use cases, agents, automation workflows, APIs, prototypes, production-ready components, evaluation harnesses, test plans, documentation, operational handoff materials, and AWS/Azure platform integrations. Responsibilities include prompt and agent engineering, retrieval and grounding, testing, debugging, deployment support, observability, DevSecOps, and information security compliance.

Designs enterprise AI solutions and reference architectures for prioritized AI Center of Excellence use cases. Responsibilities include build-versus-buy analysis, model and vendor selection, integration design, model evaluation, benchmarking, prototyping, governance alignment, security assessment, platform selection, solution reviews, and delivery-ready architecture documentation. The role also evaluates data privacy, security risks, and information lifecycle protections, including GDPR and CCPA compliance.

Build and support full-stack AI solutions using Python, AWS AI services, APIs, integrations, and agentic workflows. Responsibilities include testing, debugging, technical documentation, deployment support, production readiness, and applying information security and data privacy practices, including GDPR and CCPA compliance.

Designs, develops, deploys, and supports enterprise AI applications using AWS AI services, LLMs, generative AI, RAG, AI agents, APIs, and cloud-native architectures. Builds full-stack interfaces and backend services, integrates AI capabilities with enterprise systems, and delivers secure, scalable production solutions. Collaborates with stakeholders, data scientists, architects, product teams, and governance teams while supporting information security, privacy compliance, documentation, and agile development.

Architect and govern enterprise Azure AI Foundry environments, Azure OpenAI implementations, model access patterns, evaluation frameworks, deployment standards, and AI governance practices. Design secure, scalable, production-grade generative and agentic AI platforms; optimize performance, reliability, and costs; and collaborate with business, cloud, cybersecurity, architecture, and data teams. Translate business needs into technology solutions while supporting compliance, data protection, and enterprise AI adoption.