831 jobs for “ai engineer”
ElevenLabs
Design, build and maintain open source SDKs, client and server libraries and an MCP server to drive developer adoption, while shaping the public API and developer tooling. Acts as "customer zero" for new developer products, jumping across languages and the stack, with scope to write technical content and speak at conferences.
MCP
ElevenLabs
Build and maintain front-end and back-end components of a generative AI voice product suite used by millions, shipping end-to-end features with high ownership. Work spans Python, TypeScript/React, APIs, cloud infrastructure and large-scale datasets, collaborating with Engineering, Growth and Sales in lean autonomous teams.
Python · TypeScript · React
PhysicsX
Build and deploy customer-facing applications powered by physics AI models, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, Python/FastAPI microservices, and cloud deployment with Kubernetes, Terraform and AWS/Azure, plus quarterly travel to customer sites.
FastAPI · Helm · Kubernetes +3
PhysicsX
Lead technical delivery of physics-informed AI, architecting deep learning models and optimisation methods to predict and control physical systems. Own data pipelines and pre-processing best practices while mentoring a team and collaborating with simulation engineers and customers. Involves frequent on-site customer travel across multiple regions.
NumPy · SciPy · Pandas +2
Faculty
Lead the technical direction and delivery of complex AI projects for enterprise clients in financial and professional services, acting as primary technical authority from discovery to production. Balance hands-on full-stack work in Python and TypeScript/React with mentoring a squad of engineers and shaping reusable architecture. Distinct for its client-facing, highly regulated context and emphasis on safe, responsible AI deployment.
Python · TypeScript · React +3
Faculty
Lead the design, build and deployment of production-grade ML and software systems for clients across pharma, academia and MedTech. The role blends hands-on Python and cloud engineering with architecture decisions, client-facing advisory work and mentoring junior engineers. It sits within a cross-functional life sciences team focused on AI for therapy research and commercialisation.
AWS · Azure · GCP +2
Wayve · 11–50 people · Series A
Develops and maintains Wayve's Core Simulation system in modern C++ and Python, integrating driving-stack components, simulated robot systems and vehicle-platform capabilities. Initially focused on high-scale open-loop evaluation, the role involves debugging on-road versus simulated behaviour, improving reproducibility, observability and automated testing, and profiling simulator performance across a shared codebase.
GenAI Development Tools
Wayve · 11–50 people · Series A
Works at the boundary between onboard software and vehicle hardware, bringing up new vehicle platforms on benches, HiL systems and vehicles, including at international test locations. Builds and maintains vehicle-facing components and shared frameworks in C++, Python or Rust on Linux-based robotic and automotive systems using ROS2, CAN and Automotive Ethernet, with diagnostics, tooling and documentation for long-term supportability.
ROS2 · NVIDIA DRIVE · Qualcomm Snapdragon Ride +3
Design, build and operate core connectivity infrastructure behind external tool calls, including the MCP proxy and OAuth/token management systems. Own reliability for infrastructure other teams and partners depend on, covering SLOs, on-call, incident response and postmortems, while building enterprise admin controls and permission models and contributing to the MCP standard and its official Python and TypeScript SDKs.
MCP · OAuth · Python +4
Builds foundational infrastructure for AI safety safeguards, including data storage, metric and evaluation systems, and tooling for human and agentic review. Maintains real-time, multi-layered defenses against misuse at scale while reducing manual oversight, working across the stack primarily in Python.
Claude Code
Databricks · 1001–5000 people · Late stage
Customer-facing engineering role building and productionizing data and AI solutions on the Databricks platform for emerging enterprise and digital native accounts. You own architecture and design decisions, implement end-to-end systems spanning data engineering, ML/AI and application development, and embed with client teams. Billable delivery work with roughly 20% travel.
Databricks · Apache Spark · AWS +4
Databricks · 1001–5000 people · Late stage
Customer-facing engineering role owning architecture and design decisions while building production-grade data, AI and application systems on the Databricks platform. You embed with client teams, from technical ICs to executives, to scope and deliver end-to-end solutions, contributing reusable accelerators and product feedback. Requires hands-on coding in Python, Scala or TypeScript, deep Apache Spark and distributed computing expertise, and multi-cloud knowledge, with around 20% travel to customer sites.
Databricks · Apache Spark · AWS +7
Luminance · 51–200 people · Series C
Works across Sales, Product and Customer Success to help enterprise customers integrate Luminance's AI platform, building hands-on integrations with systems such as Salesforce, ServiceNow and Slack. Acts as the technical expert supporting Account Executives, managing integration issues and creating reusable toolkits, APIs, SDKs and customer-facing documentation.
Salesforce · ServiceNow · Slack
Cortech Talent Solutions
Hands-on full stack role building and maintaining web applications and backend services for a digital platform, working from Python services to customer-facing interfaces. You'll integrate front-end elements with server-side logic, support AI/ML and IoT-dependent systems, and work across the full development lifecycle in a small team where work reaches production quickly.
Python · React · TypeScript +7
Reperio Human Capital
Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.
Snowflake · AWS · Linux +2
