Top Artificial Intelligence Software Engineer Jobs

Lead end-to-end AI agent deployments for MSP and enterprise partners. Own discovery, scoping, integration architecture, production software development, rollout, adoption, and outcome measurement. Build reusable tools and platform components while working directly with partner IT teams and internal Engineering, Operations, Product, and GTM teams. The role requires customer-facing technical delivery, production-grade coding, and experience shipping LLM-powered systems.

Design and build immersive, interactive sandbox environments in Unity. Implement dynamic camera, animation, and large-scale addressable asset systems. Integrate Unity with AI agents for navigation and dialogue. Develop and optimize WebGL and iOS deployments. Collaborate closely with a small founding team to shape technical foundation and roadmap.

Write and optimize GPU kernels for machine learning training and inference workloads. Profile hardware performance, improve memory and scheduling efficiency, integrate kernels into training and serving systems, benchmark end-to-end results, and maintain performance across evolving hardware and frameworks. Collaborate with research teams on algorithm-kernel co-design and share low-level performance expertise across the organization.

Own and improve Attentive's first-party data collection across the JS tag, Cloudflare Workers, and Java backend. Expand edge compute capabilities, build agentic AI systems to detect and fix data-quality issues, harden the event ingestion pipeline for reliability and observability, and lead technical direction on a small autonomous team while mentoring engineers.

Partner with clinics to design and implement a Tauri/Rust desktop client and Python cloud backend, build scalable infrastructure for concurrent AI agents, manage cloud (AWS/GCP) CI/CD and container deployments, and ensure HIPAA/SOC-2 compliant security, monitoring, and secrets management.

Build and scale a fintech risk and compliance platform as the second engineer. Responsibilities include developing full-stack features, owning product areas end to end, improving reliability and performance, collaborating with customers, participating in architecture and code reviews, and establishing engineering best practices. The role requires independent feature delivery, strong full-stack fundamentals, production experience, sound technical judgment, clear asynchronous communication, and willingness to learn compliance and AI domains.

Build and ship end-to-end features for the Starbridge platform across data models, backend services, APIs, and user interfaces. Collaborate with product, design, and engineering in an early-stage, in-person startup environment. Establish scalable foundations, respond to customer feedback, make architectural decisions, and contribute to frontend, backend, cloud infrastructure, and potentially LLM-powered product features.

Early-stage B2B MarTech company seeks generalists who build and ship products across engineering, data, AI, and go-to-market. Candidates should operate in ambiguity, take ownership, collaborate closely with founders, and demonstrate shipped work via portfolios, side projects, or write-ups rather than resumes.

Build responsive Bubble.io applications for startup clients, collaborate with product managers and designers, refine requirements, test tools and assumptions, communicate with clients weekly, and contribute reusable components and tutorials to the internal library. The role offers autonomy, client exposure, and opportunities to advance into technical leadership or product management.

Build and own patient and clinician product experiences for an AI-first medical practice: real-time streaming chat, onboarding, record linking, clinician dashboards, prescription and lab workflows, accessibility-compliant mobile-first UIs, analytics, and integrations (Stripe, backend APIs). Collaborate closely with clinicians and design to deliver production React/TypeScript applications that affect real patient care.