Top AI Engineer Jobs

Build and launch full-stack features for Kapwing Studio, design and implement LLM-powered pipelines and generative model prototypes, test and monitor releases, and integrate ML-powered APIs to automate video and visual content editing.

Lead technical and scientific delivery of consumer weather verticals: translate model output into data pipelines, APIs, and product integrations; integrate LLM-driven content generation; collaborate with research scientists, product, design, and front-end teams to graduate experiments to flagship products.

Lead design, build, and operate platform-level IAM services across the stack. Define APIs, data models, and orchestration surfaces. Research and deliver Identity-for-AI capabilities and prototypes, collaborate with product and UX, mentor engineers, and support production lifecycle activities using modern AI tooling to accelerate development.

Build and operate IAM capabilities across the Ping platform: design and implement APIs, services, workflows, and orchestration. Research and prototype AI/agent identity solutions, collaborate with product and UX, participate in full lifecycle development, and support production systems while using AI tooling to accelerate engineering work.

Lead design and deployment of AI-driven predictive maintenance solutions for facilities. Analyze workflows, build/train/deploy ML models, integrate sensor/IoT data, ensure security/compliance in a classified on-site environment, validate models, run stakeholder working sessions, and provide technical documentation and training.

Lead the design and delivery of AI solutions for legal professionals. Mentor engineers, establish AI engineering practices, and ensure scalable architecture and quality across systems.

As a Senior Platform Engineer, you'll manage the infrastructure for deploying AI applications in enterprise environments, collaborating with customer IT on security and compliance.

Design, develop, and optimize algorithms for oneDNN targeting Intel processors and graphics. Conduct performance analysis and contribute to low-level tuning and optimization efforts, collaborating with cross-functional teams and engaging with the open-source community.

Design and implement full-stack applications for GenAI, build developer tooling, collaborate with product teams, and enhance AI agent delivery.

Design and implement full-stack applications and AI agents to enable rapid development and deployment of AI solutions in critical industries. Mentor engineers and take ownership of projects while applying secure SDLC practices and collaborating with cross-functional teams.

As a Senior Forward Deployed Engineer, you will embed within customer environments to develop and deploy AI solutions, enhance performance through evaluations, and become a domain expert in specific verticals.

The Lead Product Software Engineer will develop AI solutions, collaborate with teams, and lead projects focused on customer-centric product development using Agile methodologies.

As a Senior Software Engineer, you will enhance AI application interfaces for enterprise clients, ensuring high product quality and a seamless user experience through direct customer collaboration and rapid iteration.

The AI Enablement Engineer will build and deploy AI agents, design intelligent workflows, and collaborate with teams to improve processes using AI technologies.

As a Senior Software Engineer for AI products, you will own features across the stack, develop the AI SRE product, create integrations, and collaborate on user experience while ensuring technical quality.

Lead full‑stack design, development, and maintenance of scalable financial applications across front-end, back-end, and databases. Build RESTful APIs and microservices, participate in code reviews, troubleshoot production issues, mentor junior developers, and adopt AI/LLM tools and cloud/container platforms to improve delivery and security.

Design and build scalable AI knowledge and retrieval infrastructure (search, vector stores, RAG) including streaming/batch ingestion, indexing, low-latency APIs, LLM integration, observability, and platform services. Lead architecture, mentor engineers, and partner with AI, data, and product teams to enable enterprise AI assistants, copilots, and agent-based systems.

Design, develop, test, and maintain LabVIEW-based and multi-language diagnostics and calibration software for reticle inspection platforms. Prototype and productionize AI/ML and generative-AI tools to improve diagnostics, calibration, and engineering workflows. Build CI/CD pipelines, participate in design/code reviews, troubleshoot system-level issues, and collaborate with cross-functional hardware, system, and manufacturing teams. Occasional travel (~10%).

Build, optimize, and deploy production-grade generative AI applications. Design multi-agent systems and LangGraph workflows, implement advanced RAG with LlamaIndex and vector DBs, fine-tune and host LLMs, integrate/swap commercial and open-source models, and deliver scalable FastAPI/async backends with Docker, monitoring, and CI/CD.

Conduct advanced AI/ML research and develop novel models and methods (especially adversarial, safe, or agentic AI). Design, prototype, and integrate ML systems, run GPU-accelerated training, build reproducible experiments, evaluate and benchmark models, and communicate results via reports and publications. Collaborate with interdisciplinary teams and lead technical tasks for mission-focused solutions.

Lead technical vision and architecture for enterprise ML platforms and MLOps. Design training, feature, serving, and observability systems; establish ML lifecycle and governance; solve complex cross-team engineering problems; mentor senior engineers; evaluate emerging AI technologies; drive cost optimization, compliance, and organizational alignment.

Design, build, and deploy scalable ML pipelines for multimodal neuroscience data. Research, train, and deploy advanced deep learning and reinforcement learning models to predict brain states, detect pathological patterns, and generate personalized neuromodulation parameters. Select AI frameworks and cloud infrastructure, collaborate with computational neuroscientists, and contribute to IP and publications.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

Build and own backend services for underwriting and AI risk monitoring platforms. Implement end-to-end features across Next.js/React, Node.js/TypeScript, Python and Postgres. Design scalable, observable systems, mentor peers, collaborate with product, data science, and founders, and participate in in-person rapid prototyping and roadmap planning.

Build and scale a full-stack Next.js application tracking PRs, CI health, test parity, and benchmarks across AI accelerator open-source projects. Integrate GitHub APIs and webhooks, design PR/metrics schemas, visualize results, and produce technical digests and reports on cross-accelerator parity and performance trends.