Top AI Engineer Jobs

The Senior Customer AI Engineer will support enterprise customers' AI Marketing efforts, focusing on integrations, technical solutions, and optimizing customer outcomes while maintaining effective communication across teams.

Build and maintain backend, CI/CD, and data integrations for the NOS platform. Ramp on Palantir Foundry and AI/data tooling, write production code and tests, and collaborate with engineers and data scientists under senior review to deliver scoped features.

Build automated unit, integration, and end-to-end tests for NOS using AI-assisted generation and review. Translate NQA-1 regulatory requirements into traceable test artifacts and evidence. Establish defect tracking and V&V workflows, ramp on Palantir Foundry and NOS architecture, and help develop testing approaches for AI-powered features, including prompt regression and output validation.

Design and build full-stack AI prototypes; decompose products into model, retrieval, prompting, agents, and orchestration components; integrate APIs, databases, and cloud; define evaluation loops; perform error analysis; collaborate cross-functionally; and present results to founders and partners.

Lead end-to-end AI/ML projects: build, deploy, and maintain LLM/NLP and ML models in production. Translate business needs into technical plans, collaborate cross-functionally, apply MLOps and observability best practices, and improve model performance and reliability.

Design, build, and deploy agentic multi-agent AI systems and RAG pipelines for document intelligence and procurement workflows. Integrate and evaluate LLMs, implement orchestration frameworks, build human-in-the-loop approvals, and collaborate on production deployment, observability, and secure architectures for government acquisition environments.

The AI Engineer will develop innovative products using AI to enhance insurance operations by leveraging LLMs and structured data extraction.

As a Senior AI Engineer at Blank Metal, you'll lead the architecture and strategy for AI projects, ensuring system reliability and scalability while mentoring other engineers and translating business needs into technical solutions.

Develop and implement AI features, integrate LLM APIs, collaborate on system design, and mentor junior engineers in a production environment.

Citizen Health seeks AI/Machine Learning Engineers to develop AI solutions for healthcare using advanced ML techniques, focusing on rare diseases and patient care. Responsibilities include designing ML models, optimizing LLMs, and ensuring compliance.

Own finance data infrastructure, system integrations, and AI automation for FP&A and the monthly close. Design and maintain EPM architecture, BigQuery/dbt pipelines, iPaaS integrations, data governance, and automated close/forecasting pipelines. Build AI/LLM-driven agents with human-in-the-loop controls to ensure SOX-compliant, reliable outputs.

Lead Software & AI Engineer responsible for designing, developing, and deploying software solutions integrating AI/ML. Requires extensive experience in cloud-native development and DevSecOps.

Senior technical leader responsible for the success of complex enterprise AI deployments: setting architecture and evaluation strategy, ensuring production reliability, coaching and developing engineering leads, partnering with customer executives, debugging critical issues, and scaling pilots to enterprise deployments while using AI-native engineering practices.

Design, build, deploy, and operate production AI systems for customers. Implement end-to-end AI workflows (models, prompts, agents, retrieval, evaluators), write maintainable Python services, monitor and debug live systems, create evaluation and observability tooling, and work closely with stakeholders to iterate systems for reliability and business value.

Build and own an agentic creative pipeline that generates, vets, and optimizes thousands of image and video ad variants daily: extend LLM critic feedback to multimodal assets, build fast cost-efficient video pipelines, route generative models by cost/quality, train and deploy brand-style checkpoints, implement policy pre-flight checks, and ship event-triggered ad pipelines with A/B validation in production.

Lead technical delivery and architecture of production AI systems for enterprise customers. Mentor engineers, integrate models/agents with customer data and APIs, operate and improve live systems, measure and debug failures, and drive pragmatic, reliable deployments that deliver business outcomes.

Build, train, test, deploy, and maintain AI models (LLMs, RAG, agentic workflows). Collaborate with engineers and product owners to implement MLOps/DevSecOps, cloud data foundations, event-driven integrations, and secure AI-enabled applications to support Air Force mission needs.

Design, train, test, deploy, and maintain AI/ML models and agentic workflows (LLMs, RAG). Build secure cloud data foundations on AWS, implement MLOps/DevSecOps (CI/CD, containerization, automated testing), design event-driven integrations, and collaborate with cross-functional teams to deliver AI-enabled solutions for Air Force mission needs. Secret clearance required.

Design, train, test, deploy, and maintain AI/ML models and agentic workflows. Build secure cloud data foundations (AWS), implement MLOps/DevSecOps (CI/CD, containers, automated testing), design event-driven integrations, and collaborate with engineers, data scientists, and product owners to deliver AI-enabled mission solutions for the Air Force. Requires Secret clearance and a relevant bachelor’s degree.

Lead and manage an onsite Edge AI Applications Lab to design, fabricate, and deploy tiny-ML models on microcontrollers and embedded platforms. Oversee lab projects, hardware prototypes, sensor data collection, model development, and cross-functional/customer collaborations. Mentor junior engineers, manage procurement and scheduling, and optimize real-time edge solutions for consumer, industrial, and automotive applications.

Design, develop, and deploy AI/ML models and production systems. Collaborate with cross-functional teams, mentor engineers, and ensure model performance, scalability, and reliability. Drive technical strategy for AI solutions.

The Principal Applied AI Engineer will lead the design of AI systems for finance, focusing on predictive modeling, intelligent automation, and software engineering best practices. They will oversee AI initiatives, mentor technical teams, and ensure compliance with financial standards and practices.

Design, develop, and deploy ML and deep-learning solutions (including generative AI). Lead end-to-end model lifecycle, build RAG/agentic workflows, integrate models into production, collaborate with engineering and clients, monitor performance, and document experiments and data provenance.

Lead development of an agentic AI platform: build agent orchestration, RAG/CAG pipelines, embeddings and vector-store ops, integrate LLMs (Anthropic Claude primary), deliver full-stack features across Python/Node/React, own production deployments, evaluation pipelines, and mentor a small senior engineering team while working hybrid in Denver.

As a Senior Consultant, you will design and develop AI solutions using Anthropic models, support client engagements, and lead automation efforts while collaborating with delivery teams.