Top AI Engineer Jobs

As an Applied Gen AI Engineer, you'll design and deploy generative AI systems for code review, collaborating to enhance developer productivity through advanced workflows and models.

Build components of an AI Account Manager to automate hosting and optimization for advertiser accounts. Develop diagnosis and recommendation models using LLMs and delivery history, implement observability, dry-run safeguards, and evaluation pipelines, and collaborate with senior engineers and product to ensure reliable, auditable optimization that preserves account health and drives revenue.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

The Forward Deployed Engineer interfaces directly with customers to assess and resolve security issues, delivering tailored AI and data-driven solutions, while documenting processes for broader application across customers.

As a Principal AI Engineer, you'll design scalable AI systems, mentor teams, develop large-scale LLMs, and optimize AI-driven cybersecurity solutions.

The Associate Director, AI Engineer will design and develop multi-agent systems, collaborate with teams, and implement AI workflows for clients.

The AI Engineer IV will lead the development and implementation of AI systems, influence architecture decisions, mentor team members, and ensure best practices in a hybrid work environment.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

Build, refine, and scale production agent systems: multi-step tool-using agents, memory systems, proactive agents, and evaluation frameworks. Ensure fast, predictable, traceable behavior and uptime while working across infra, frontend, and product.

The AI Engineer will design and build AI systems using LLMs, develop agent workflows, implement APIs, and collaborate with teams to optimize AI applications.

Lead development and deployment of AI-first systems: build generative and discriminative models, enable multimodal behavior classification from mobile signals, define prompting and benchmarking standards, own ML tooling and SDLC, and partner with Product and Engineering on the AI roadmap.

Design, develop, and implement AI/ML models, manage AI solutions on cloud platforms, and collaborate with teams to optimize models.

The GCP GenAI Engineer will design and implement Generative AI solutions on Google Cloud, focusing on deployment, security, and connectivity, while supporting CI/CD pipelines and infrastructure as code.

Seeking a Senior-Level AI Engineer to design and maintain LLM orchestration frameworks, integrate AI/ML tooling, and support security assessments.

The Mid-Level AI Engineer will develop AI tools, integrate various systems, manage LLM models, and support security assessments and certification processes.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

Design and build an AI platform to resolve insurance claim denials, develop AI agents for workflows, and improve system performance. Collaborate closely with billing managers to understand workflows and contribute to the team's AI/ML vision.

This role involves leading AI projects, designing and deploying AI systems, collaborating with stakeholders, and developing tools to enhance efficiency in healthcare applications. The engineer will mentor junior members and iterate on prototypes until widely adopted.

As a Forward Deployed Engineer Lead, you will lead the technical strategy and execution of AI applications, collaborate with teams, and ensure reliable deployments.

As an Applied AI Engineer, you will build and ship AI features, optimize ML models, ensure production reliability, and collaborate with cross-functional teams.

As a Senior AI Engineer, you'll design and develop scalable SaaS applications using Java, focusing on AI and data infrastructure, collaborating with teams.

Design, build, and operate AI/ML capabilities for satellite operations including multi-agent systems, RAG pipelines, vector DBs, time-series anomaly detection and failure prediction, containerized AWS deployments, CI/CD, observability, human-in-the-loop workflows, and on-call production support.

As an AI Engineer, you will enhance backend systems for agentic AI features, design and deploy multi-agent systems, and manage state and context workflows.

Lead the design and development of advanced AI agents for cybersecurity, focusing on real-time decision-making and adaptive threat responses, while mentoring teams and collaborating across functions.

The Senior Machine Learning Engineer will develop and maintain algorithms/services for multi-agent AI, deliver cloud-native architecture, and optimize ML models for performance.