Top AI Engineer Jobs

Lead design and implementation of an edge-native intelligent processing platform integrating SDRs, edge AI, distributed inference, resilient P2P communications, containerized services, CI/CD/DevSecOps, and cloud/embedded integrations while mentoring engineers and supporting demos and documentation.

Develop full-stack, AI-first MDM features using Java and modern JavaScript (React/Angular). Build responsive UIs, design REST APIs, write unit/integration tests, debug front-end and backend systems, and apply AI tools to accelerate development and improve code quality. Participate in Agile ceremonies and collaborate across Product, UX, QA, and Platform teams.

Join Travelers as a Software Engineer I to perform end-to-end engineering tasks using AI-driven tools across the software lifecycle. Responsibilities include design, development, testing, debugging, monitoring, incident resolution, and documentation. The role emphasizes continuous application of AI tooling, prompt engineering fluency, steady delivery, domain understanding, and collaborative problem solving.

Design, implement, test, and maintain cloud-native software solutions. Troubleshoot complex defects, build APIs and integrations, enable AI/LLM capabilities, mentor junior engineers, contribute to CI/CD and observability, and collaborate with cross-functional teams to deliver reliable systems.

You will build agentic AI products across web, backend, and iOS, owning features end-to-end and mentoring junior teammates.

Design, develop, and maintain enterprise full‑stack applications; implement AI/ML pipelines and RAG systems; ensure DOE compliance and hardened security; collaborate with infrastructure and security teams; support CI/CD, containerization, and production incident response.

Lead design and delivery of production-grade generative AI platform capabilities. Drive architecture and system design, implement cloud-native, containerized solutions (Python, Kubernetes, Terraform), ensure CI/CD, observability, and secure-by-design practices, and lead cross-functional stakeholder and engineering efforts to deliver enterprise AI applications.

Design and run full-spectrum red team operations across corporate, lab, OT, cloud, and AI environments. Develop offensive toolchains, build scripts and exploits, execute end-to-end attack chains, emulate adversaries based on threat intel, and collaborate with IR, threat intel, and detection engineering to convert findings into durable detections and defenses.

Own post-sale technical delivery for enterprise AI solutions: onboard customers, assess data readiness, design AI workflows, deploy and integrate with enterprise systems, ensure security and compliance, define success metrics, and drive adoption, expansion, and ongoing customer success.

Lead design, development, testing, and App Store submission of production-scale iOS features in Swift. Collaborate cross-functionally, enforce code quality via reviews and refactoring, maintain technical documentation, and adopt AI-assisted tooling to improve productivity across large, user-facing modules.

Post-sales technical lead for a portfolio of education institutions driving adoption of OpenAI products. Own account health, enablement, deployment, use-case validation, multi-workstream program management, executive and technical stakeholder alignment, and measurable student, faculty, and institutional outcomes.

Design and build scalable backend services and APIs for HPE EdgeConnect Orchestrator, integrate AI/LLM-driven workflows and Copilot capabilities, work with analytics and telemetry for real-time insights, and ensure quality through testing, debugging, and performance optimization.

Lead design and build of Generative AI infrastructure and tools, deploy large-scale ML/LLM models to production, enable scalable ML pipelines on heterogeneous hardware, collaborate with product and data science, lead cross-team architecture and technical discussions, manage projects, and mentor engineers.

Develop infrastructure and tools to integrate Generative AI into enterprise applications. Build scalable end-to-end ML pipelines on heterogeneous hardware, collaborate with data scientists to train/fine-tune models, lead product development for the Generative AI suite, mentor junior engineers, and own production deployments.

The role involves managing enterprise AI platforms, supporting IT operations, security initiatives, and enhancing AI tooling efficiency through proactive support and coordination.

This role focuses on developing AI/ML algorithms for various applications, requires teamwork with developers and researchers, and involves analyzing datasets and deploying ML models.

Lead enterprise-scale AI/ML delivery for Intelligence Community customers, managing program execution, compliance (RMF/ATO/IATT), governance, cross-functional teams, vendor coordination, and Agile delivery from concept through production. Provide executive briefings, reporting, risk management, capture and proposal support, and ensure secure classified deployments.

Lead ML/AI analytics across STARZ telemetry and operational data to detect anomalies, forecast trends, and surface actionable signals. Build repeatable signals frameworks, apply anomaly detection/classification/clustering/time-series models, leverage generative AI/LLMs for summarization and RCA, define alerting and escalation, partner with engineering and product, and mentor junior analysts.

Develop and maintain AI-driven features, design scalable data structures and pipelines, and enhance platform capabilities while collaborating with teams.

Lead design and delivery of production-grade AI-powered full‑stack features, integrating LLMs, agent systems, vector databases, and RAG. Build scalable frontend (React/Next.js) and backend (Python/Go) services, cloud-native infrastructure, CI/CD pipelines, and observability. Influence architecture, mentor teams, and drive technical vision from 0-to-1 through ongoing ownership.

Lead design, build, and production of agentic AI systems: architect agent workflows, memory, orchestration, and evaluation frameworks. Provide technical leadership, mentor engineers, and deliver reliable, observable AI features integrated with data platforms.

As a Forward Deployed Engineer, you will develop AI agents and automation workflows, collaborate with teams, and ensure secure, reliable solutions integrating with various systems.

Design and productionize ML models and agentic systems for intraday financial alpha generation. Build data pipelines, experiment frameworks, and portfolio optimization methods. Collaborate with quants and engineers to move models from research to live trading environments.

Build agentic, reasoning-driven systems on top of LLMs; own full-stack AI product features from prompt design to orchestration, tooling, monitoring, and UX. Prototype with design, run LLM evaluation and A/B tests, integrate emerging methods, and collaborate directly with founders and customers to deliver product-facing AI features.

The role involves designing AI/ML solutions for national security, capturing user workflows, and integrating systems in classified environments, requiring collaboration with various stakeholders.