Top AI & Machine Learning Jobs

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.

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.

Design, deploy, and operate production AI agents and generative AI solutions using Azure OpenAI, Snowflake, Databricks, retrieval, semantic models, and tool orchestration. Build reliable data workflows, governance, security, monitoring, evaluation, and responsible AI controls for sensitive healthcare data. Integrate AI systems with enterprise applications and APIs, troubleshoot performance and retrieval issues, and collaborate with technical and business stakeholders to deliver compliant, scalable solutions.

Leads the development and production deployment of machine learning, generative AI, LLM, RAG, and agentic AI solutions for pharmacy and healthcare operations. Builds predictive models, scalable data pipelines, AI services, vector search systems, and healthcare analytics using large clinical, claims, EHR, provider, member, and operational datasets. Establishes model monitoring, evaluation, guardrails, responsible AI practices, and regulatory compliance while collaborating with clinical, product, business, data, and engineering teams.

Leads the architecture, development, deployment, and operation of enterprise AI Ops solutions, including RAG pipelines, agentic workflows, and AI-powered applications. Improves SRE practices, leads incident response, automates cloud infrastructure with Terraform and GitHub Actions, and ensures reliability, scalability, security, and responsible AI. Designs and operates software using Python and Node.js, manages Kubernetes environments, mentors engineers, and leads globally distributed technical teams.

Provides technical leadership for enterprise Generative AI and Agentic AI initiatives. Designs scalable AI platforms, foundation-model solutions, RAG and knowledge systems, multi-agent workflows, and LLMOps capabilities. Establishes architecture standards, governance, evaluation, observability, security, and responsible AI practices while optimizing quality, performance, scalability, and cost. Leads complex delivery, mentors AI professionals, influences enterprise roadmaps, and drives adoption of reusable frameworks and shared services.

Lead enterprise AI/ML engineering for Medicare & Retirement, defining AI strategy, building scalable MLOps platforms, embedding GenAI and ML into products and operations, ensuring responsible AI and compliance, and delivering measurable business value through production-grade AI solutions and platform transformation.

Lead design, development, and deployment of GenAI and NLP solutions using LLMs, vector search, and RAG. Architect agentic AI workflows, optimize inference and pipelines, perform advanced data preprocessing and feature engineering, and collaborate across research, engineering, and product teams to productionize ethical, scalable AI systems.