Top AI Engineer Jobs

In this role, you will design and develop AI-native applications, managing the lifecycle of high-scale AI systems using LLMs and generative AI to enhance customer experiences.

Partner-facing engineer who designs, builds, evaluates, debugs, and launches high-utility plugins for ChatGPT and Codex. Own partner technical journeys, write prototypes and production code, review architectures for security/privacy/reliability, run evaluations, and improve platform APIs, SDKs, docs, and tooling to support smooth launches and ongoing maintenance.

Early-career Data & AI Engineer supporting client work and applied R&D. Prepare, clean, and validate heterogeneous data; build reproducible Python/SQL workflows; support ML and generative-AI tasks (embeddings, RAG, evaluation); prototype tools; document assumptions; participate in code review and translate project lessons into reusable assets.

Own the technical vision and system architecture for Digit’s safety-critical perception systems in dynamic environments. Lead architectural tradeoffs across sensing, ML models, redundancy, latency, compute, and robustness. Define verification and validation standards, support safety cases and hazard analysis, evaluate emerging technologies, and collaborate with navigation, controls, hardware, and safety teams. Mentor senior engineers and represent perception architecture to executives, customers, regulators, and partners.

Develop and evaluate AI/ML-driven automation for ASIC and VLSI design and implementation. Explore GenAI, reinforcement learning, graph neural networks, and convolutional networks to optimize power, performance, area, and quality. Build prototypes, pilot automation on real SoC and IP designs, and collaborate with architecture, design, verification, implementation, academic, and industry teams. Contribute to CAD methodologies, tools, and digital transformation initiatives for advanced automotive processors and microcontrollers.

Partner with Account Executives on technical discovery, solution positioning, demonstrations, RFPs, and proofs of concept. Design and configure AI-native CPQ solutions, including product catalogs, configuration rules, pricing logic, and CRM or ERP integrations. Explain AI behavior and quoting workflows to technical and non-technical audiences. Collaborate with Product, Engineering, Demo, and Forward-Deployed teams while building expertise in applied AI, CPQ, and quote-to-cash technologies.

Conduct research and engineering across computer vision, vision-language models, 3D perception, and physical AI. Build and fine-tune perception and multimodal models, develop perception-to-action policies, curate datasets, design evaluations, run rigorous experiments, and deploy reproducible services using modern AI infrastructure. The role translates published research into prototypes and production-ready modules for robotics, simulation, video understanding, and embodied intelligence.

Develop production-grade Python services, pipelines, testing frameworks, and data tools that automate quantitative market and credit risk model lifecycles. Build AI/ML and LLM-enabled documentation, data quality, validation, and workflow capabilities within governed enterprise environments. Collaborate with quants, validators, data engineers, and program leaders while applying secure software engineering, CI/CD, testing, and scalable design practices. Mentor junior developers and contribute to technical design reviews.

Designs and owns full-stack AI developer productivity products and platforms, including desktop applications, backend APIs, data pipelines, dashboards, telemetry, integrations, and developer tools. Leads technical design for scalable AI coding tool integrations, translates ambiguous requirements into production software, and manages reliability, observability, performance, security, and supportability. Evaluates human- and AI-generated code and advances prompt engineering and system-context practices for reliable AI-assisted development.

Build and maintain production internal tools, web applications, integrations, AI agents, MCP servers, and automation systems across Finance, Accounting, Legal, People, Recruiting, and Sales. Own projects end to end, automate billing and revenue processes, integrate internal systems with ERP and Salesforce, enable business users to create automations, and measure business impact.

Lead applied AI research from literature review and foundational research through proof-of-concept development and production deployment. Design and evaluate machine learning, deep learning, reinforcement learning, NLP, computer vision, and prediction models for business-critical challenges. Provide technical leadership, mentorship, strategic direction, and cross-functional collaboration while driving innovation and translating research into measurable business impact.

Lead the architecture and technical strategy of Stord’s AI platform while building agent orchestration, tool systems, prompt management, integrations, and stateful edge services. Ship reliable LLM-powered features, guide AI-assisted development, establish engineering quality standards, mentor engineers, manage technical risks, and collaborate with product, data science, ML, and engineering teams.

Build and shape an agent-orchestration platform using frontier LLMs. Transform heterogeneous enterprise program data into structured, queryable knowledge, develop reliable and observable backend services, and own features from design through production. Collaborate with product management and customers, make prioritization decisions, review code, write tests, and support production systems. The role requires strong Python backend skills, LLM production experience, cloud expertise, and comfort solving ambiguous startup problems.

The Senior Software Engineer will explore AI solutions in healthcare, having experience in full-stack/backend development and startup culture.

As a Senior Software Engineer at Whatnot, you'll build AI tooling for internal use, developing workflows and infrastructure to enhance software delivery. You'll collaborate across teams to gather feedback and prioritize features in a rapidly evolving landscape.

Build the core AI platform and high-performance Rust backend powering an AI-native trading copilot. Implement streaming responses, low-latency tool execution, caching, orchestration of models and tools, secure APIs, auditing/tracing, and safe, auditable trading action infrastructure. Partner with product and frontend to enable AI-native UX and translate trading domain requirements into resilient platform primitives.

Build and maintain scalable full-stack web applications across front-end and back-end systems. Develop RESTful APIs, integrate AI and machine-learning models using Python, manage SQL and NoSQL databases, and create GitHub Actions CI/CD pipelines. Collaborate with data scientists, troubleshoot and improve existing software, participate in code reviews, and apply modern DevOps, cloud, containerization, and microservices practices.

Leads software engineering efforts for production applications, including development, testing, deployment, monitoring, security, resilience, and performance tuning. Designs reusable code and architecture documentation, collaborates with product teams, supports agile delivery, and mentors junior engineers. Contributes to technical roadmaps, cross-functional initiatives, platform adoption, system modernization, and AI-driven engineering productivity improvements.

Lead definition and standardization of next‑generation wireless system architecture across 3GPP, GSMA and TM Forum. Drive AI/ML and autonomous network integration, represent the company in standards bodies, define AI observability and agent frameworks, and produce actionable standards and architecture guidance for cloud‑native core networks and future 6G services.

Own optimization algorithms for scheduling, resource allocation, constraint satisfaction, and conflict resolution. Build analytics for defects, yield, throughput, and manufacturing intelligence. Productionize optimization and ML systems, integrate and fine-tune LLMs for cloud, air-gapped, and edge environments, and partner with manufacturing, quality, and planning experts to model operational constraints.

Architect and develop scalable AI-driven IVR, conversational, NLP, and LLM solutions for high-volume customer interactions. Build classification and clustering models, perform SQL-based analysis, design RAG and agentic workflows, and establish LLMOps practices for monitoring and lifecycle management. Partner with platform, speech engineering, and product teams while mentoring junior and offshore engineers.

Build and own mobile experiences for clinicians using Flutter, Swift/iOS, and Kotlin/Android. Develop AI-native workflows involving real-time transcription, ambient documentation, multimodal inputs, offline functionality, and intelligent recommendations. Collaborate with clinicians, product, design, AI, and backend teams from discovery through launch. Ensure performance, accessibility, reliability, analytics, testing, observability, and release readiness while contributing to mobile strategy and mentoring engineers.

Support U.S. government and public-sector customers by troubleshooting complex SaaS and OpenAI platform issues, handling escalations, and translating security and compliance requirements into actionable guidance. Partner with Engineering, Product, Operations, and Go-to-Market teams to resolve recurring problems, improve products, and develop scalable support processes. Use Python, AI tools, automation, and scripting to reduce manual work and improve operational efficiency. Provide occasional holiday and weekend on-call coverage.

Support U.S. government and public-sector customers using OpenAI products, troubleshooting complex SaaS and platform issues under FedRAMP requirements. Serve as an escalation point, communicate technical resolutions, partner with Engineering and Product, and develop Python scripts, AI-powered workflows, and automation to improve support operations. The role includes customer calls, incident support, operational improvement, and occasional holiday or weekend on-call coverage.

Build and operate AI infrastructure systems, including telemetry pipelines, observability dashboards, incident-management automation, hardware and software catalogs, service ownership data models, and self-service discovery tools. Lead cross-functional infrastructure initiatives and develop AI-assisted operational tooling. The role requires production software and infrastructure expertise, programming experience, and the ability to improve reliability, visibility, incident response, and operational efficiency across NVIDIA GPU cloud environments.