Top AI Engineer Jobs

The Staff Level AI Engineer will innovate applied AI methods, enhance user experience through AI, and architect AI infrastructure for a SaaS platform, collaborating across product and engineering teams to drive business value.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Design, build, and operate production-grade agentic AI systems and LLM-powered features for financial workflows. Implement RAG pipelines, tool invocation, agent orchestration, vector storage, monitoring, and shared AI infrastructure while ensuring reliability, security, auditability, and regulatory compliance.

Lead research and prototype development for generative AI and emerging technologies. Design architectures, build prototypes and proofs-of-concept, evaluate external partners, and collaborate across teams to translate research into production-ready recommendations and solutions.

Lead a team to design, build, and deploy AI-powered product management tools and multi-agent systems. Implement MCP infrastructure, production observability, and scalable integrations with enterprise platforms. Drive adoption, governance, and AI-enabled operating models while partnering across Product, Engineering, Risk, and Governance to measure impact and ensure responsible use.

As a Senior Applied AI Engineer, you will design, build, and maintain AI systems using LLMs and backend services, ensuring reliability and performance in production. Responsibilities include developing workflows, monitoring AI behaviors, and collaborating across teams to enhance engineering standards.

Lead the development of AI systems integrating computer vision and language understanding, focusing on reinforcement learning and multimodal AI architectures.

The Senior Forward Deployed AI Engineer will create, deploy, and maintain AI systems, optimize workflows, and communicate with customers to address needs within production environments.

As a Senior Staff Applied AI Engineer at Databricks, you will design and build retrieval systems, optimize search for both LLMs and humans, and lead technical direction and team growth.

Develop and maintain end-to-end LiDAR and camera perception software for robotics platforms. Responsibilities include sensor drivers, ROS 2 packages, GPU-accelerated processing, calibration, synchronization, recording and playback tools, Docker environments, packaging, CI/CD, hardware-in-the-loop testing, and production release automation. The engineer will support integration issues and collaborate closely with hardware, silicon, algorithm, manufacturing, and customer teams.

Leads end-to-end delivery of production AI and machine learning solutions, owning architecture for LLM, RAG, embeddings, vector databases, and APIs. Mentors engineers, translates business needs into scalable technical solutions, oversees MLOps, CI/CD, monitoring, and reliability, conducts code reviews, and collaborates with stakeholders. The role remains hands-on through prototyping, troubleshooting, and development support.

Build and scale production AI systems, APIs, data pipelines, retrieval systems, and model-serving infrastructure for consumer and clinician-facing health products. Integrate and fine-tune LLMs and other models, manage AI feature lifecycles from prototyping through monitoring, and ensure reliability and observability. Collaborate with engineering, product, and science teams. More senior candidates may lead AI architecture, roadmap development, and mentoring.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Lead technical direction and people for an AI/ML engineering squad to design, build, and deploy production-grade ML and Generative AI (LLMs, RAG, agentic systems). Drive MLOps, CI/CD, model monitoring, Responsible AI compliance (HIPAA/PHI), architecture reviews, and mentor 5–10 engineers to deliver secure, production solutions.

Serve as senior technical advisor to strategic partners for Arm-based Edge AI SoC solutions. Lead system-level architecture, IP selection, integration, optimization, technical engagements, demonstrations, and cross-functional resolution to drive design wins and product adoption while providing customer feedback to influence product roadmaps.

As a Graduate Engineer, you'll design and develop AI agents and features while learning finance operations, coding best practices, and developing APIs in a collaborative environment.

Develop AI agents for finance workflows, design APIs, enhance engineering practices, ensure data security, and facilitate user collaboration.

Lead technical strategy and architecture for CoreWeave's orchestration platform (SUNK). Own critical orchestration components, drive cross-org initiatives in scheduling, quota enforcement, and hyperscale scaling. Mentor senior engineers, establish reliability and observability best practices, and ensure workloads run reliably and efficiently for large GPU ML training and inference clusters.

Own technical delivery of Moveworks AI Agents for enterprise customers: gather requirements, design and build integrations and automations, tune LLM-based solutions, advise on AI roadmaps, synthesize feedback to product, and create reusable templates to scale implementations.

Designs, develops, and deploys production Generative AI and LLM applications, including RAG pipelines, AI agents, semantic search, backend APIs, and enterprise data integrations. Builds scalable data and MLOps solutions using Databricks, Snowflake, and AWS. Collaborates across engineering and data teams while optimizing model performance, cost, latency, security, compliance, and privacy, including HIPAA requirements where applicable.

Build and operate agentic AI tutoring systems, including multi-step tutoring loops, tool use, learner memory, planning, verification, guardrails, and evaluation harnesses. Develop evidence-backed learner models and measure conversational and teaching quality using real learner data. Partner with the founding team to define product behavior, translate ambiguous questions into measurable systems, and deliver end-to-end improvements. The role requires production LLM experience, strong Python or TypeScript/Node.js skills, and independent software engineering ownership.

Build and scale the LLM orchestration and retrieval systems powering Qualitate’s AI Moderator. Responsibilities include designing multi-turn agentic interview pipelines, optimizing model routing and retrieval quality, building production APIs and microservices, creating evaluations, monitoring and guardrails, processing unstructured data, and delivering structured research insights. The role partners closely with product, data engineering, research, and the founding team in an in-person New York City startup environment.

The Staff AI Engineer will design and implement production agents for construction plan reviews, focusing on efficient data handling and improved permit processing. Responsibilities include operationalizing workflows, evaluating systems, collaborating on UX, and ensuring reliability and quality in AI products.

Develop AI-enabled tax solutions by enhancing the TRAM system, improving data pipelines, and collaborating with tax experts for model refinement.

Leads the design, development, testing, and deployment of enterprise automation, RPA, AI/ML models, intelligent agents, APIs, integrations, and data pipelines. The role supports cloud and infrastructure operations through improved reliability, financial accountability, asset optimization, productivity, and data-driven decision-making. Responsibilities include establishing engineering standards, testing, security, governance, CI/CD practices, technical documentation, troubleshooting, Agile delivery, mentoring junior engineers, and collaborating with stakeholders.