AI Full-Stack Engineer Jobs

View detail

As the first US based Engineer, the role entails acting as the technical bridge between the product vision and customer reality. Responsibilities include designing, architecting, and shipping full-stack features that solve customer compliance challenges, owning the technical relationship with key customers by implementing solutions, gathering requirements, and translating feedback into product improvements. The engineer will build scalable services and APIs for the LLM compliance platform, make high-impact technical decisions quickly while being accountable to engineering standards and customers, challenge assumptions about what and how to build, and shape the product roadmap and engineering practices as the company scales from Series A to market leadership. The work combines coding, customer engagement, and steering product direction with high autonomy and collaboration with the founding team.

View detail

The Software Engineer on the Workspace & Observability Team at Anyscale is responsible for building user-facing application features for the Anyscale AI platform, focusing on the backend to implement the core business logic of these features. Responsibilities include interacting with users to understand their requirements, designing and implementing features, maintaining and improving these features over time, and working on observability tools that help users monitor and debug AI applications running on distributed clusters. Specific projects may involve developing the Ray Dashboard observability tool, library-specific observability tools like the Ray Train and Ray Serve dashboards, a unified log viewer for querying logs across a Ray cluster, and anomaly detection features to automatically identify and suggest fixes for performance bottlenecks or bugs. The role also involves collaborating with distributed systems and machine learning experts, communicating work through talks, tutorials, and blog posts, and contributing to building and shaping the company.

View detail

Design, architect, and operate scalable services and APIs that power the LLM compliance platform. Architect how AI insights are surfaced to users, ensuring the system is robust, fast, and intuitive. Make high-impact technical decisions quickly. Challenge "why" and "how" to ensure delivery of the best possible experience for users. Shape engineering culture, standards, and tooling as the company grows. Own end-to-end technical decisions including designing systems, architecting solutions, shipping to production, and iterating based on customer feedback.

View detail

Work on a small, high-caliber team building AI products for clients, from requirements gathering and prototyping through system design, development, testing, and deployment. Own features end-to-end and develop domain expertise across a range of AI use cases. Spend most of the time coding and frequently interact with clients to ensure the solutions meet their needs.

View detail

You will work on a small, high-caliber team building AI products for clients, setting technical direction, writing code, and serving as the go-to person when challenges arise. Spend approximately 75% of your time coding and 25% interacting with clients, including CTOs, to understand problems, evaluate tradeoffs, and ensure solutions meet their needs.

View detail

Work on projects such as developing a product that root causes KTLO work and recommends solutions, building a software catalog that works for monoliths and is user-friendly, and helping protect engineering focus time by systemically solving sources of distraction or mental load with AI.

View detail

Debug and fix issues in the platform and ship PRs with fixes. Build internal tools and copilots powered by generative AI to enhance the team. Rapidly prototype proof-of-concepts for customer use cases. Collaborate across Engineering, Product, and Solutions teams to unblock customers and drive AI adoption.

View detail

Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.

View detail

Own and lead Baseten Voice AI product areas end-to-end, including architecture, system design, implementation, rollout, and long-term production operations. Design, build, and operate real-time, large-scale, high-performance model-serving systems for STT, TTS, and voice agent workloads with clear service level objectives for mission-critical customer deployments. Drive cross-team collaboration with sister engineering teams to address full-stack technical problems, align priorities, and coordinate end-to-end delivery across the product surface. Mentor teammates through code reviews, design documentation, and provide technical leadership.

View detail

Contribute to building Reinforcement Learning Environments (RLE) and supporting infrastructure; implement features across backend systems and frontend interfaces; work with senior engineers to improve system reliability and performance; help build modular workflow domains such as engineering, finance, and legal; support data pipelines that power model training and evaluation.