Top AI Engineer Jobs

The Principal Software Engineer will lead the design and build-out of an AI Context Layer, ensuring high-quality data for AI systems, while managing access control and developer interfaces, and leading cross-team projects.

The role involves designing infrastructure for distributed architectures, managing CI/CD pipelines, collaborating with engineering teams, securing cloud and application layers, and enhancing automation and developer productivity.

Design and build secure, cloud-native AI applications using LLMs, RAG, and Amazon Bedrock to provide AI-assisted search, summarization, and clinical question-answering; integrate with enterprise healthcare systems using FHIR/HL7, implement vector search and prompt orchestration, ensure Fed security/privacy compliance and CI/CD, and support testing, monitoring, and governance for production readiness.

Design, train, test, deploy, monitor, and maintain ML models (including LLMs/generative AI) for national security missions. Collaborate with data engineers, software developers, data scientists, and stakeholders to apply ML algorithms, triage large datasets, and deliver production-safe, mission-critical AI/ML solutions.

Design and implement AI/ML solutions (LLM-powered, agentic, or hybrid) for cyber and intelligence workflows. Capture user processes, integrate AI with APIs and enterprise data stores, ensure production reliability and security in classified environments, and collaborate with operators and leadership to deploy mission-ready capabilities.

Embed with strategic higher-education partners to design, build, and ship production AI and platform integrations (LLM/RAG, LTI) across Cengage products. Own end-to-end deployments, write production code, ensure compliance and accessibility, evaluate AI safety and outcomes, mentor FDEs, and translate field learnings into product roadmap contributions.

Lead systems engineering design activities for digital applications in cardiology, ensuring compliance with regulations and managing product requirements throughout the development lifecycle.

Build and maintain Databricks-based data pipelines, analytics layers, dashboards, and internal AI applications for the ISV partner organization. Own metrics, monitoring, governance, and self-serve reporting; prototype partner-product integrations and provide feedback as an early adopter to product and DevRel teams.

As a Software Engineer in Frontier AI Infrastructure, you'll design secure systems for the public sector, improve engineering standards, and collaborate with cross-functional teams to meet government requirements. You'll also participate in customer engagements and contribute to the product strategy while ensuring compliance with federal regulations.

Develop and implement AI models and algorithms using Azure technologies, focusing on full-stack development, AI solutions, and collaboration with stakeholders to optimize business processes.

Lead the design and optimization of batch and streaming data pipelines, ensuring high-quality data delivery for AI and analytics, while mentoring and promoting engineering best practices.

Design, build, test, deploy, and operate end-to-end AI/ML pipelines for mission systems. Implement RAG (document and graph), build LLM-based automation and multi-agent solutions, fine-tune open-source models, containerize workloads, and collaborate across cross-functional teams while maintaining security requirements.

Build and ship end-to-end AI-native product features, prototype with modern AI models/APIs, collaborate with product/design, maintain fast reliable systems, and improve dev workflows and deployments.

Designs, develops, tests, and maintains complex multi-technology applications. Gathers requirements, leads change requests, performs design and code reviews, mentors teammates, coordinates on-call support, evaluates vendors, and proposes technical solutions and enhancements.

Senior engineer responsible for end-to-end application and system development, technical design and code reviews, requirements gathering, change request ownership, testing and deployment, on-call coordination, mentoring, and leading small-to-medium projects across multi-technology platforms.

Lead technical discovery and solution design for enterprise MedTech customers, translate claims data into commercial insights, deliver data via secure sharing/APIs/warehouses, own RFPs and security reviews (SOC2/HIPAA/BAA), enable demo environments and AI narratives, and institutionalize best practices across Sales, Product, Data, and Engineering.

Lead technical strategy and architecture for large-scale, cloud-native content platforms. Design distributed backend systems, integrate LLM-powered capabilities into production, ensure availability, latency, security, and cost efficiency, drive cross-org alignment, and mentor engineering talent to achieve operational excellence and responsible AI practices.

Design, build, and ship production AI agents and ML systems for retail merchandising, document understanding, retrieval/ranking, and evaluation. Own full model lifecycle from research to production, build evaluation/observability, and collaborate with engineers, PMs, and store owners to drive measurable merchant impact.

Lead design and implementation of company-wide security architecture, perform penetration testing and vulnerability management, automate security tooling and CI/CD scanning, build observability and incident response systems, and collaborate across teams to scale security for AI compute and research infrastructure.

Lead technical architecture and delivery of end-to-end AI solutions across the Workday ecosystem. Design data flows, integrations, security and RAG/LLM patterns; advise executive stakeholders; lead technical workstreams; collaborate with Product and Engineering; ensure privacy, ethical AI, and scalable deployments for complex global customers.

Develop and maintain secure, cloud-native AI features and integrations for ontology-based applications. Migrate cloud platforms, integrate multiple data streams, implement backlog requirements, apply DevSecOps practices, and work on an agile scrum team to deliver scalable, tested software using containerization, microservices, CI/CD, and LLM/RAG-enabled capabilities.

Lead design and implementation of scalable DevOps platforms, architect CI/CD pipelines, manage IaC, optimize platform performance and security, automate deployments, collaborate with cross-functional teams, and mentor engineers.

Lead developer advocacy for AI and agentic security: advise security companies, accelerate NVIDIA stack adoption, guide partner integrations, map ecosystems, collaborate cross-functionally, run community events, and feed product teams with field insights.

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Lead and define organization-wide Responsible AI, evaluation, and model-governance standards. Orchestrate cross-organization AI initiatives, influence engineering and executive stakeholders on architecture and roadmap, oversee end-to-end delivery, and mentor other program managers to drive strategic AI program outcomes and safety requirements.