Top AI Engineer Jobs

The Senior AI/ML Applications Engineer will develop, integrate, and support AI-driven tools for IC design and verification, focusing on agentic AI methods to enhance productivity.

The Principal AI Compiler Engineer will design and enhance an AI compiler toolchain, integrating AI for optimizing neural network deployment on SoCs, partner with hardware teams, and improve performance through diagnostics and profiling.

The Full Stack Developer will implement OpenAI and GPT-3 tools to develop processes for creating content and editing media for podcasts.

Lead design and implementation of an AI-native web platform, owning web framework, design system, CMS, CI/CD, infrastructure and SDLC agents. Define architecture, pioneer agentic workflows, set evaluation guardrails, mentor engineers, and drive cross-team technical alignment and migrations.

Lead development of AI-assisted engineering tooling and infrastructure so agents can autonomously run in cloud dev environments, access CI/CD and internal systems, execute tests, and improve developer productivity through integrations, documentation, and enablement.

Own and evolve Syndi, an agent runtime powering in-product chat and integrations. Design, ship, and operate core runtime surfaces (agent loop, tool execution, memory, context), build eval systems, ensure observability and reliability, review consumer integrations, and implement compliance and legal requirements for production LLM systems.

Build and maintain production-grade React+TypeScript web interfaces for data-intensive, real-time AI products. Own end-to-end frontend features, optimize UI performance for large datasets, collaborate with design and backend teams, establish frontend best practices, improve architecture and tooling, and resolve production issues across browsers and devices.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

Owner/implementer of end-to-end full stack features for data-intensive AI products: design and build scalable Node.js backends, REST APIs, and React+TypeScript frontends; optimize performance; establish testing, observability, and CI/CD; collaborate with product, design, and ML teams; debug and support production systems.

Build and maintain full-stack product features, backend services, APIs, data pipelines, and AI integrations to transform customer interaction data into AI-powered experiences. Collaborate with cross-functional teams to design, test, and support production systems, internal tools, and user-facing interfaces. Own ambiguous problems end-to-end and raise engineering quality across the data and AI platform.

Embedded with strategic customers, own end-to-end design, build, and production rollout of cloud infrastructure for large-scale GPU/HPC AI workloads. Build compute orchestration, platform services, onboarding sandboxes, and reliability/security tooling. Turn field learnings into reusable platform capabilities and partner with Product and Engineering to productize them.

As a Senior Staff Software Engineer, you will develop and maintain AI deployment software, optimizing hardware-software co-design, and work closely with various experts to enhance infrastructure.

Lead design, implementation, and deployment of scalable AI/ML systems for aerospace and defense. Develop RAG, embedding/retrieval pipelines, transformers, GANs, RL and MPC-aligned models. Use GPU/HPC for real-time decisioning, mentor engineers, ensure safety, validation, regulatory and cybersecurity compliance, and support integration and prototyping.

Conduct AI research to develop new approaches, algorithms, and methodologies for portfolio companies; influence technical direction, drive AI system improvements, and collaborate with founders to accelerate growth and impact.

Research and develop ML and statistical algorithms for networking, edge computing, cybersecurity, and autonomy. Build and evaluate simulation-driven solutions, lead subsystem software development, create automated tests, and contribute to proposals and technical plans while presenting results to customers and senior staff.

Lead integration of AI into transportation products: prototype models, evaluate third-party tools, design fine-tuning/benchmarking strategies, oversee computer vision asset extraction, and apply AI to QA/QC with cross-functional teams to improve data integrity and product fit.

Design, evaluate, and deploy production AI agents that combine LLMs, retrieval, memory, and traditional ML. Build retrieval and memory pipelines, multi-agent systems, evaluation frameworks, and production guardrails. Run experiments and ablation studies, collaborate with infrastructure and enterprise customers, and measure business impact while ensuring reliability, safety, and observability.

Design, evaluate, and deploy production AI agents combining LLMs, retrieval, memory, and tool use. Build retrieval/memory pipelines, multi-agent systems, evaluation frameworks, and production engineering for reliable, safe enterprise AI deployments while partnering directly with customers.

Design, evaluate, and deploy production frontier AI agents that combine LLMs, retrieval, memory, tool use, and traditional ML. Build retrieval and memory systems, multi-agent coordination, evaluation frameworks, and production engineering (reliability, observability, safety). Partner with enterprise customers to translate problems into scalable AI architectures and run experiments to measure business impact.

The Senior Software Engineer will lead the development of AI solutions for the life insurance sector, overseeing full stack application design and delivery while guiding junior engineers.

Design, develop, deploy, and maintain AI/ML models and pipelines. Collaborate with cross-functional teams, implement MLOps and CI/CD, monitor model performance, investigate incidents, ensure compliance with security/privacy/ethical requirements, and document model architectures and procedures.

Develop and execute test plans for AI models; identify and analyze defects and anomalies; implement automated evaluation frameworks (dataset checks, API tests, CI/CD); define AI quality metrics (accuracy, latency, fairness, cost); collaborate with development teams to improve model performance; analyze test results and provide actionable recommendations to enhance model accuracy and reliability.

Design, develop, train, validate, and deploy AI/ML products for life-sciences customers. Advise leadership on technical and commercial feasibility, collaborate with cross-functional and commercial teams, and lead projects in RL, LLM agent harnesses, fine-tuning, governance, and model evaluation.

Design, build, and operate the C3 Agentic AI Platform for production AI agents. Architect scalable, reliable distributed systems; improve agent accuracy, performance, and safety; implement guardrails, auditability, and rollback; collaborate with data scientists and product owners; own end-to-end projects and mentor junior engineers.

Lead design and engineering of enterprise AI-powered automation using n8n as an orchestration platform. Build scalable, secure API-first and event-driven integrations, AI-enabled workflows and agents, CI/CD and governance, observability, and reusable automation frameworks. Provide technical leadership, mentor engineers, and drive platform standards and operational excellence.