Top AI Engineer Jobs

Owns the company-wide IT and cybersecurity program, including SOC 2 compliance, cloud security, penetration-test remediation, business continuity testing, endpoint management, access controls, onboarding and offboarding, AI security governance, vendor reviews, security training, incident response, and employee IT support. The role partners with engineering, HR, Finance, leadership, auditors, and healthcare customers while managing security across AWS, Heroku, Cloudflare, Google Workspace, GitHub, and related tools.

Partner with business stakeholders and IT delivery teams to design, implement, and deploy AI-enabled production applications, integrations, and data pipelines. Focus on solution feasibility, deployment, operationalization, and driving adoption. Support benchmarking and internal development across divisions (travel up to 50%).

Design, build, and operate cloud-scale, multi-tenant services for Microsoft Edge and Copilot App management. Lead architecture, cross-team integrations, reliability, security, and production operations. Mentor engineers, drive technical direction, and use telemetry and customer feedback to improve enterprise management and AI-powered productivity experiences.

Develop, test, deploy, and maintain .NET-centric web applications using C#, Angular 17+, and Azure. Build and consume REST APIs, work with SQL Server, source control, CI/CD pipelines, and collaborate on code reviews, debugging, performance optimization, and third-party integrations.

Develop and validate system-level software for neuromorphic accelerator platforms, including device-driver interfaces, OS integration, runtime APIs, simulation environments, and tooling for profiling, debugging, benchmarking, and validation. Collaborate with hardware, architecture, and application teams to enable platform features, improve performance, and ensure robust functionality for production deployments.

Design, build, and operate a secure, high-performance agent sandboxing platform. Ensure isolation, reproducibility, and efficient resource use across containerized/virtualized environments. Improve developer experience (APIs, client SDKs, docs), debug and monitor production incidents, lead architecture and end-to-end projects, and collaborate with internal teams to shape roadmap and tooling.

Lead enterprise AI transformation by discovering opportunities, designing and building scalable LLM/agent-based workflows, architecting data and integration solutions, partnering with cross-functional stakeholders, and driving production delivery and adoption across business units.

Ship and operate an LLM-backed dissolution support product: design retrieval, tool contracts, structured outputs, observability, and safe human handoffs; build versioned evaluations, privacy/tenant safeguards, rollout/canary plans, and iterate on production failures to improve product reliability and customer outcomes.

Design, develop, and productionize ML and LLM-based systems: implement models, build and optimize data pipelines, run experiments and A/B tests, deploy and serve models (containers/APIs), ensure code quality and reproducibility, and collaborate across engineering and systems teams while maintaining security and compliance for classified environments.

Direct AI coding agents to build and ship marketing sites, maintain brand voice and design discipline across five brands, own SEO and information architecture, run competitive research, and review/correct AI-generated code and copy to ensure production-quality outcomes.

Design and implement scalable AI/ML-driven HealthTech microservices, contribute to technical architecture, write high-quality code, perform code reviews, develop proofs-of-concept, troubleshoot production issues, and document work while collaborating in agile teams.

Lead end-to-end MEP design and delivery for hyperscale and modular HPC/AI data centers (50–300 MW), focusing on integrated electrical, mechanical, and plumbing systems, high-density liquid cooling, MV/LV power distribution, modular architectures, compliance with industry codes, and mentoring junior engineers through design, procurement, construction, commissioning, and handover.

Designs, develops, tests and maintains complex multi-technology applications; leads requirements gathering, code and design reviews, change requests, on-call coordination, mentoring, and small-to-medium projects while proposing technical solutions and vendor evaluations.

Design, build, and deploy AI-driven automation pipelines using workflow orchestration and agent frameworks to replace manual workflows. Integrate LLMs, APIs, and internal systems, ensure logging, security, and observability, and collaborate cross-functionally to productionize and maintain reliable automation solutions.

Lead architecture and implementation of production-grade agentic systems integrating LLMs across applications. Drive LLM integration strategy, cognitive automation roadmap, scalable distributed system design, best practices, cross-functional alignment, and mentor engineering talent.

Lead design and implementation of scalable, production-grade agentic systems that integrate LLMs, drive LLM integration strategy and cognitive automation roadmap, ensure reliability and observability of distributed ML systems, collaborate cross-functionally, and mentor senior engineers.

Build and ship end-to-end AI-native product features across frontend, backend, and infrastructure. Integrate LLMs and agentic workflows with email, calendar, docs, and tools, design polished UX, and develop suggestion engines and workflow builders for web, desktop, and mobile. Influence product direction as an early, in-office hire.

Join Hiring.Cafe as a Founding Machine Learning/AI Search Engineer to develop AI recommender systems and scalable infrastructure, contributing to a transformative job search engine.

Develop and operate a system for argumentation related to AI safety, utilizing ontologies and knowledge graphs while collaborating with various stakeholders.

The Research Engineer will develop AI platforms focusing on alignment challenges, multi-agent systems, and optimization algorithms while collaborating on technical publications and prototypes.

Develop and maintain LLM pipelines, design RAG architectures, implement agentic systems, and integrate AI features into data pipelines.

The Software Engineer - AI Systems will design and implement systems to coordinate LLMs, build testable software stacks, conduct research, and collaborate with team members to create AI-powered security solutions.

Design and implement cybersecurity controls, assess vulnerabilities and mitigation strategies, integrate security across the SDLC, run security assessments and audits, review security tool outputs to identify threats, support deployment and administration of IAM/PAM/endpoint/DLP/encryption technologies, and document processes.

The Staff Software Engineer will lead the development of cloud-native AI platforms, optimizing AI workload deployment in Kubernetes environments and collaborating with cross-functional teams.

Design, build, and deliver an AI and machine learning platform, enhancing developer velocity while collaborating with cross-functional teams.