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.

Design and build AI solutions using Microsoft AI stack (Azure, Copilot Studio, Azure AI Foundry). Develop copilots, RAG and agentic workflows; create API services, implement secure data access, and build CI/CD pipelines. Collaborate with product, engineering, security, and business teams to deliver compliant, observable, and scalable AI capabilities for utilities.

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.

The Staff AI Engineer will design and implement production agents for construction plan reviews, focusing on efficient data handling and improved permit processing. Responsibilities include operationalizing workflows, evaluating systems, collaborating on UX, and ensuring reliability and quality in AI products.

The Senior AI Engineer will design and improve AI pipelines, build evaluation frameworks, optimize performance, and collaborate with teams to integrate AI capabilities into Brellium's platform.

Design and build AI-driven systems, analyze large datasets, optimize LLM performance, manage business stakeholder projects, and ensure production-grade analytics solutions.

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.

Design, build, and deploy LLM-powered tools, RAG-based knowledge systems, and agentic workflows to automate SOC integration tasks. Own reliability, evaluation, and observability for AI systems and collaborate with SOCD teams to scope, validate, and measure productivity gains from deployed automation.

Translate multi-modal AI research into 0-1 products: design and run ML experiments, build scalable training and evaluation infrastructure, implement MLOps and data pipelines, deploy models, and use AI code tooling to move experiments to production MVPs.

Design, build, and operate production LLM-driven agents that crawl, extract, and verify web evidence to enrich business identities. Own classification, discovery, linkage, risk scoring, shared agent infrastructure, model/tool selection, prompt engineering, eval methodology, and cost/latency optimizations for real-time enrichment pipelines.

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

Design and operate cloud network infrastructure on Azure and AWS, build AI platforms, oversee infrastructure-as-code, and ensure security compliance.

As a Senior Staff Applied AI Engineer at Databricks, you will design and build retrieval systems, optimize search for both LLMs and humans, and lead technical direction and team growth.

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 AI Engineer will analyze business processes for automation opportunities, design and maintain RPA solutions, and develop Intelligent Document Processing systems while collaborating with stakeholders and ensuring reliability of solutions.

As a Senior AI Engineer at Via, you will lead the development of AI products, collaborate with partners, design scalable systems, and shape the technical culture of a new team.

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

As a Data/AI Engineer Intern, responsibilities include data analysis using AI tools, model development, and collaborating with stakeholders to address business challenges.

Develop AI-enabled tax solutions by enhancing the TRAM system, improving data pipelines, and collaborating with tax experts for model refinement.

The AI Engineer will develop AI/ML solutions for investment analysis, design applications, optimize models, and work with large datasets in healthcare and finance contexts.

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

The Senior Applied AI Engineer will build production-grade AI systems, collaborating with cross-functional teams to ensure impactful care solutions while leading engineering initiatives and mentoring team members.

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

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.

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