Top AI Engineer Jobs

Lead or support integration and testing of spacecraft hardware in lab and cleanroom environments. Create AI&T flows, develop and execute test procedures, use test and measurement equipment and GSE, document results, identify risks and facilities needs, and coordinate with systems engineers and external partners during spacecraft acceptance and launch operations.

Lead and execute spacecraft assembly, integration, and test (AI&T) campaigns; define test strategies and AI&T flows; manage facilities, GSE, cost/schedule estimates; author proposals; mentor engineers and technicians; ensure quality, risk mitigation, and operational success in cleanroom and lab environments.

Design and implement cloud-native AI/ML solutions on AWS. Build LLM and RAG architectures using Transformers, PyTorch, TensorFlow, LangChain. Develop in Python and Golang, contribute to open-source projects, and apply AWS services (Bedrock, SageMaker, ECS, Lambda).

Build and maintain backends and clinician tooling, integrate LLMs and custom models into production, design evals and observability, implement safety/fallback strategies, and support product expansion across clinical apps.

The Embodied AI Engineer will deploy VLA models on physical robots, validate them in simulation, and ensure they meet production reliability standards while handling real manufacturing challenges.

As the Founding GTM AI Engineer, you will create AI-driven solutions to enhance revenue-generating workflows, build automations, and analyze sales data to inform strategies.

Designs and maintains automated UI, API, integration, regression, and end-to-end tests for traditional and LLM-powered applications. Builds LangSmith evaluation datasets, evaluators, tracing, annotation workflows, and regression suites for LangGraph agents. Integrates tests and evaluations into CI/CD quality gates, analyzes nondeterministic failures, monitors production quality, and collaborates with users, QA, engineering, product, and business stakeholders to expand coverage and improve software delivery practices.

The Founding AI Engineer will develop Vantager's AI-native platform, optimize financial task performance using LLMs, and improve AI systems through instrumentation and data processing.

As an AI Engineer, you will design and build full-stack applications for AI-driven workflows, collaborate with diverse teams, and optimize user experiences.

As an AI Engineer, you will build and optimize AI agents for enterprise-grade conversations, collaborating with cross-functional teams to improve performance and integrating systems with AI models.

The Software Engineer will develop and maintain LLM orchestration frameworks, optimize data pipelines, and collaborate on AI tools and security processes.

As a Backend Engineer, you'll design, code, and ship full-stack features, integrate APIs, and ensure robust backend systems while collaborating closely with researchers and users.

The AI Engineer will design and build production systems, focusing on LLM integration, system reliability, evaluation frameworks, and high-quality product features while maintaining strong engineering practices.

The Senior Staff AI Engineer will lead the design and optimization of reinforcement learning systems for enterprise applications, focusing on scalable architectures and production deployment. Responsibilities include mentoring, collaboration, and ensuring compliance with AI ethics and safety standards.

The Founding AI Engineer will build production AI systems for nuclear deployment, focusing on fine-tuning, R&D, and collaborating with top tech partners. Responsibilities include designing eval infrastructure, owning fine-tuning pipelines, and pushing the frontier of AI applications relevant to nuclear operations, ensuring high-quality outputs and continuous improvement.

The AI Engineer will develop AI-powered revenue platforms, work on AI infrastructure, approval workflows, and intelligent collections agents, focusing on reliability and customer needs.

Design, develop, and deploy scalable software systems focusing on Python, collaborate with teams to solve complex problems, and optimize system performance.

The Full Stack AI Engineer will build and deploy AI-integrated MVPs, develop front-end and back-end systems, optimize ML pipelines, and maintain APIs and cloud infrastructure, focusing on healthcare administration.

As a Full Stack AI Engineer, you'll build AI applications and products, prototype solutions, and collaborate with founders in a fast-paced environment.

As a Senior AI Engineer, you will architect AI systems for marketing, build generative pipelines, and ensure compliance with privacy standards, all while leading MLOps processes.

Lead AI Engineer to mentor teams, guide AI solution design, ensure code quality, and manage complex AI projects while evaluating new technologies.

Build and deploy AI agents and automations to streamline commercial and operational workflows. Work with stakeholders to identify opportunities, prototype LLM-based solutions, integrate via REST APIs, and maintain documentation and monitoring. Serve as technical liaison to business teams and iterate quickly on deployed tools.

Lead enterprise model-training strategy for Commercial AI products: fine-tune LLMs (QLoRA/LoRA/PEFT), train traditional ML models, design large-scale data pipelines, enforce data governance and PII handling, build reproducible experiment/training pipelines, optimize GPU/distributed training costs, and mentor teams to operationalize models into production.

Lead design and implementation of the enterprise AI orchestration and retrieval platform: build MCP servers, define tool-surface and multi-agent patterns, design RAG systems and chunking, implement routing/context/window management and observability, set evaluation and safety standards, onboard product teams, and mentor engineers to raise orchestration and retrieval maturity.

The role involves developing AI applications for VLSI design using machine learning and related technologies. Duties include infrastructure design, AI solution implementation, collaboration with teams, and maintaining design databases.