Top AI & Machine Learning Jobs

Leads design, development, testing, deployment, and maintenance of cloud-native enterprise applications and APIs. Builds Java and Python backend services, React-based front ends, microservices, CI/CD pipelines, and Azure infrastructure. Develops agentic AI and RAG solutions, supports AI lifecycle operations, and ensures secure, scalable, high-quality delivery. Provides technical leadership, mentorship, architecture guidance, production troubleshooting, and continuous improvement across Agile teams.

Leads the design, development, and deployment of AI-powered healthcare solutions using Java, Spring Boot microservices, HL7 FHIR, Da Vinci guides, Kafka, relational databases, Docker, Kubernetes, and cloud platforms. Builds REST APIs and event-driven systems across claims, eligibility, prior authorization, and provider domains. Establishes CI/CD automation, observability, security, and responsible AI practices while evaluating emerging technologies and improving operational workflows.

Leads enterprise data and AI engineering strategy across business units. Responsibilities include modernizing cloud data platforms, establishing governance and semantic layers, enabling self-service and AI-powered analytics, building reusable data products and models, and supporting machine learning, generative AI, RAG, and agentic AI architectures. The role manages data engineering, architecture, AI engineering, and analytics enablement teams while partnering with executives and business stakeholders to deliver trusted, scalable data capabilities.

Design, develop, deploy, and maintain AI/ML models and LLM-powered conversational agents for pharmacy and benefits experiences. Build multi-tool workflows, APIs, cloud infrastructure, conversation memory, personalization, evaluation systems, and reusable AI platforms. Support production reliability through CI/CD, observability, debugging, governance, and secure practices for regulated healthcare environments.

Design and deliver production-grade Agentic AI and Generative AI platforms integrated with MCP servers and LLMs. Build secure AI services, API gateways, microservices, identity and access controls, cloud infrastructure, and Terraform automation. Establish CI/CD and testing standards, collaborate with architecture, security, and product teams, evaluate emerging AI technologies, conduct code reviews, and mentor engineers. The role is fully remote within the United States.

Lead architecture and technical strategy for an agentic AI claims automation platform. Define end-to-end architecture, enable multi-agent workflows, integrate models and MLOps, ensure governance, resilience, observability, and cost efficiency, and mentor architects while aligning with enterprise AI standards.

Develop and deploy AI and machine learning solutions, analyze complex enterprise datasets, build predictive and optimization models, conduct statistical experiments, and translate findings into business recommendations. The role includes applying deep learning, NLP, generative AI, and ethical AI practices; creating scalable decision-support frameworks; evaluating emerging technologies; collaborating across teams; and mentoring junior data scientists and analysts.

Lead end-to-end generative AI and machine learning initiatives, designing secure and scalable architectures, developing and deploying advanced models, analyzing healthcare data, conducting experiments, and establishing MLOps processes. Research emerging AI methods, promote responsible AI practices, and mentor or recruit AI and machine learning talent. Collaborate with software engineers to productionize models and deliver reusable capabilities for healthcare solutions.

Leads enterprise AI strategy and architecture while developing production-ready machine learning, deep learning, Generative AI, and Agentic AI solutions. Designs LLM, RAG, semantic search, vector retrieval, and orchestration workflows; establishes evaluation, governance, guardrails, and MLOps practices; and transitions validated solutions into production. Mentors applied data scientists, leads small technical teams, builds reusable frameworks and accelerators, and influences enterprise AI standards and adoption.

Leads data scientists, analysts, and engineers integrating pricing models into an enterprise pharmacy pricing platform. Provides technical leadership across solution design, platform integration, production delivery, analytics architecture, and software engineering. Manages resources, coaches team members, partners with product, engineering, and business leaders, drives continuous improvement, and communicates analytical results and predictive models. The role requires Python and SQL expertise, people management, enterprise production delivery, financial modeling, and Agile experience.