Top AI Engineer Jobs

The Lead AI Data Engineer designs and optimizes ETL/ELT pipelines, mentors team members, collaborates on data models, and implements best practices in data governance and security.

The position requires a mid-level software engineer to assist with daily responsibilities, specializing in AI/ML development, integration, and large-scale data systems.

Lead Software Engineer responsible for architecting and building AI-native identity management and authentication systems, ensuring scalable and secure solutions.

Design and implement full-stack applications and AI agents for the GenAI platform, ensuring rapid development and deployment across critical industries. Collaborate with teams to deliver secure and reliable cloud-native systems.

The Product Frontend Engineer will design and build AI-driven applications, collaborate with teams, and ensure code quality and performance.

Design and implement microservices-based applications, collaborate with cross-functional teams in an Agile/SAFe environment, and develop clean, testable code following DevSecOps practices.

The Senior AI Software Developer will design and develop microservices-based applications, collaborate in Agile environments, and implement automation solutions. Key responsibilities include coding, integrating services, and supporting CI/CD practices.

As an AI Software Developer, you'll design and implement microservices-based applications in an Agile environment, collaborating with cross-functional teams and ensuring software delivery follows best practices including CI/CD and DevSecOps.

The AI Build Engineer Manager will lead the development of reusable AI solutions, oversee technical governance, and ensure enterprise architecture standards while integrating advanced AI technologies and cloud services.

Design, develop, and deploy enterprise-grade AI solutions; build integrations (AI Gateway, orchestration, MuleSoft); apply DevSecOps; evaluate models, data quality, and bias; collaborate with architects, engineers, and stakeholders to operationalize and improve the AI platform.

Support data engineering teams by benchmarking Matillion's AI Assistant (Maia) against manual ETL/ELT workflows. Measure productivity, speed, accuracy, quality, and maintainability; produce reports, documented workflows, and demos; and recommend best practices for integrating AI-assisted tools into cloud data pipelines.

The Execution Engineer will build AI-enabled delivery workflows and applications, using traditional coding and low-code platforms while ensuring strong engineering discipline and collaboration.

The Principal Software Engineer will architect and build core platform systems for Physical AI development, focusing on high-performance data services and collaboration with AI and Robotics teams.

Design, develop, and optimize oneDNN features and algorithms for Intel CPUs and GPUs. Perform low-level performance analysis, assembly-level tuning, multithreading and vectorization, collaborate across teams, and engage with the open-source community.

Lead architecture, development, deployment, and monitoring of generative AI applications. Build ML pipelines, model optimization (LoRA/QLoRA), guardrails, monitoring, and onboarding frameworks. Collaborate with product and data teams, mentor engineers, ensure production reliability, and drive feature development.

The AI Solutions Engineer at Cook Medical develops production-grade AI systems, collaborating widely, integrating with enterprise data, and ensuring ethical compliance.

The Research Engineer will design and implement innovative approaches to marketing measurement, build production systems, and develop algorithms to solve complex marketing attribution problems.

As an AI Product Engineer, you'll design and implement AI companion features, working closely with researchers to create user-centric products from concept to production, iterating based on user feedback.

The role involves onboarding and supporting customers using Inkeep's AI-powered solutions, creating technical resources, and leveraging AI to improve efficiency.

The AI Research Engineer will conduct research in AI, develop algorithms, collaborate with teams, and publish findings. Responsible for advancing AI methodologies in products.

Architect and develop firmware and microcontroller subsystems for AI infrastructure products, ensuring customer needs are met and firmware features are optimized.

Join Encord as a Senior Full-Stack Engineer to build tools for physical AI data stack, tackle complex problems, and improve AI training data quality.

As a Backend Software Engineer, you will design, build, and maintain backend services and APIs for automated knowledge systems, collaborating with cross-functional teams.

Design, build, and run large-scale backend and data infrastructure; productionize and run experiments on AI/ML models; implement MLOps best practices (versioning, monitoring, alerting); improve model accuracy, speed, and cost; and drive engineering process and culture improvements.

Lead design and delivery of enterprise AI knowledge bases, RAG pipelines, and AI-ready data platforms on Azure. Build ingestion, vector/graph models, backend APIs, and ML pipelines; mentor engineers and partner with investment teams to operationalize LLM-driven analytics and ensure governance, observability, and performance.