Top AI Engineer Jobs

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.

The Senior AI Engineer will develop and deploy multi-agent systems, automate workflows, integrate enterprise systems, and mentor junior engineers while ensuring quality and security compliance.

Serve as the primary technical partner to BXCI AI: assess portfolio company AI readiness, develop strategies, build prototypes and internal tooling, lead technical diligence of partners, and oversee execution of AI integrations across portfolio companies.

Serve as the primary technical partner to BXCI AI, assessing portfolio companies' AI readiness, developing strategy, building rapid prototypes and internal tooling, leading technical diligence of partners, and overseeing execution of AI integrations and deployments across the portfolio.

This role leads data and AI engineering strategies for R&D, oversees a team of engineers, and ensures compliance with regulatory standards while fostering innovation and collaboration across functions.

Provide SETA support and technical advisory for AI-enabled applications: design, prototyping, integration, and evaluation of LLMs, RAG, agentic workflows, orchestration frameworks, and evaluation harnesses. Review architectures, assess technical risks (latency, reliability, observability, guardrails), develop prototypes and guidance, support test & evaluation, and coordinate with engineers, product leads, mission users, and government stakeholders.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

Lead an embedded AI squad from discovery to production: harden and deliver AI prototypes, design reusable agentic AI patterns, ensure security and data governance, integrate AI with enterprise systems, codify reference implementations, mentor engineers, and measure outcomes to scale solutions.

The Senior Staff Software Engineer will enhance software products, guide team members, ensure application quality and safety, leverage AI tools, and participate in all aspects of the SDLC, requiring extensive experience and mastery of relevant technologies.

Hands-on Senior AI Engineer who develops, prototypes, validates, and scales AI-enabled engineering capabilities across hardware, software, and firmware teams. Build RAG/LLM/agent workflows, integrate AI with repos, CI/CD, test and lab systems, establish rigorous evaluation and governance, and convert pilots into reusable engineering platforms.

Leads enterprise architecture, technical strategy, and evolution of GEICO’s Generative AI, virtual agent, and agentic workflow platforms. Designs scalable systems for retrieval, knowledge management, prompt and context management, orchestration, semantic search, and action execution. Evaluates technologies, establishes GenAI application standards, guides production deployments, influences business strategy, mentors senior engineers, and serves as a final technical authority across multiple teams and business domains.

Manage and govern the Microsoft 365 AI and automation platform (Power Platform, Copilot Studio, Azure AI). Own architecture, environment strategy, DLP and connector governance, integration with Azure and enterprise systems, monitoring, cost control, security compliance, and a Power Platform & AI Center of Excellence while partnering across infrastructure, security, and business teams.

Build and operate custom AI agents for private-market clients end to end, from discovery and requirements through deployment, rollout, adoption, and ongoing iteration. Design agentic systems with retrieval, context design, tool and MCP integrations, orchestration, evaluation, observability, and cost controls. Work directly with clients, make product and engineering trade-offs, manage cloud infrastructure, document solutions, train users, and mentor less experienced engineers.

Build and improve Swayable’s AI and analytics engine using Python, scientific computing, machine learning, and distributed systems. Develop scalable, high-performance software, optimize parallel computing architecture, productize AI and data analysis capabilities, and collaborate with engineers, data scientists, and researchers. The role also includes designing new features, maintaining testable code, mentoring junior engineers, documenting decisions, and providing technical feedback.