Top Artificial Intelligence Software Engineer Jobs

Develop and maintain scalable backend services for an AI platform, integrate and optimize LLM and generative AI technologies, build APIs on Google Cloud, and improve performance and reliability for real-time customer engagement workflows. Collaborate with marketing, sales, and product teams while proposing innovative backend and AI solutions in a fast-paced startup environment.

Designs, develops, and maintains scalable cloud-based healthcare software platforms. Responsibilities include architecting Azure systems, building APIs and microservices, optimizing databases, developing AI-enabled capabilities, implementing CI/CD and containerized deployments, applying healthcare security controls, and collaborating across engineering, product, business, and healthcare teams.

Build and improve Clad’s construction management software across the full stack. The role involves shaping product direction, developing new products and features, influencing business and team decisions, and contributing to a high-craft, continuously learning engineering culture. The position uses TypeScript across React, Remix, and Node.js and requires working in person in New York City.

Design, build, and operate core data and streaming platform capabilities for edge and hybrid environments. Own ingestion, contextualization, streaming, schemas, contracts, validation, lineage, and internal telemetry systems. Build connectors for OT/IoT and enterprise systems, ensure reliability/observability, support production readiness, and partner with engineering and customer teams to scale durable data capabilities for AI and operations.

Build large-scale compute infrastructure for agent sandboxes, including microVM virtualization, control-plane scheduling, block-device storage, egress proxying, network isolation, and resilient hybrid cloud and on-premise systems. The role involves scaling clusters to support up to one million concurrent VMs and operating large fleets of isolated environments.

Build and own the full-stack platform powering AI-driven insurance claims automation. Collaborate with customers, design, and product strategy to shape product direction, develop claim interfaces and portals, create auditable agent workflows, and deliver reliable production systems. Responsibilities span data modeling, backend and frontend development, observability, deployment, and ongoing performance improvement. The role requires in-person work in New York and experience operating LLM- or agent-powered products at scale.

Develop and ship production software for automotive retail platforms using AI-assisted development workflows. Responsibilities include writing technical specifications, reviewing and testing AI-generated code, ensuring security and maintainability, optimizing AI tooling costs, solving moderately scoped problems, participating in on-call rotations, and collaborating with engineering, product, and design teams.

Build and maintain scalable, high-performance backend systems. Own complex engineering projects from planning through deployment, collaborate with product and customer teams, and contribute to technical direction through coding, architecture, code reviews, and mentoring. The role suits an independent senior engineer comfortable in a fast-paced, product-focused startup environment.

Build and operate reliable backend systems for complex government and enterprise data integrations. Responsibilities include designing bidirectional integrations, asynchronous workflows, retries, idempotency, observability, operational automation, debugging production systems, and creating reusable reliability patterns. The role involves TypeScript and Node.js development, database work, partner collaboration, mentoring, and improving support efficiency in a fully remote environment.

Lead architecture and hands-on development for cloud data optimization products and Stratusphere’s data platform. Diagnose and improve database, query, storage, networking, and workload performance across AWS, Azure, relational, analytical, search, and lakehouse systems. Build production services, integrations, testing, observability, and infrastructure automation while safely overseeing AI-assisted development. Partner with product teams, forward-deployed engineers, and customers to validate optimizations, document tradeoffs, and convert repeatable solutions into scalable platform capabilities.