Top AI Engineer Jobs in Boston, MA

Designs, develops, deploys, and supports large-scale AI systems, including foundation-model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. The role optimizes AI infrastructure for scalability, latency, throughput, cost, and hardware utilization; defines reliability objectives; leads architecture and technical reviews; and mentors engineering staff.

Design, develop, deploy, and optimize foundational AI systems, including large language model inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture, cost-performance optimization, technical standards, and design reviews for scalable production AI systems. Mentor senior technical staff and contribute to the long-term roadmap for responsible AI infrastructure.

Design, develop, deploy, and optimize foundational AI systems, including LLM inference, agentic workflows, vector search, guardrails, model evaluation, and orchestration pipelines. Lead cost-performance governance, technical design reviews, AI standards, roadmap development, and mentoring. Apply advanced optimization techniques to improve scalability, latency, throughput, hardware utilization, and inference costs while ensuring responsible AI deployment.

Design, develop, deploy, and support production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize model performance, scalability, latency, throughput, hardware utilization, and cost. Architect multi-model orchestration pipelines, lead technical governance and design reviews, define AI engineering standards, and mentor senior technical staff.

Design, build, deploy, and support scalable AI systems, including foundation models, LLM inference, agents, similarity search, guardrails, evaluation, governance, and observability. Optimize AI infrastructure for cost, latency, throughput, reliability, and hardware utilization. Own complex system architecture, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to long-term AI roadmaps, and mentor senior technical staff.

Design, develop, deploy, and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, and observability. Lead architecture, cost-performance governance, AI standards, and design reviews while mentoring senior technical staff. Partner with research, engineering, product, and program teams to establish foundational AI roadmaps and deliver scalable, responsible systems.

Designs, develops, deploys, and supports foundational AI systems, including LLM inference, agentic workflows, vector search, model evaluation, governance, and observability. Optimizes large-scale AI systems for cost, latency, throughput, scalability, and hardware utilization. Leads architecture and design reviews, establishes AI engineering standards, drives technical roadmaps, and mentors senior AI engineers.

Design, develop, optimize, deploy, and support foundational AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead optimization of production AI systems for scalability, latency, throughput, hardware utilization, and cost. Architect multi-model orchestration pipelines, establish governance standards, lead design reviews, contribute to technical roadmaps, and mentor senior AI engineering staff.

Design, develop, deploy, and support foundational AI systems, including LLM training and inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, reliability, and hardware utilization. Own complex system architecture, define AI service-level objectives, lead technical reviews, ensure security and compliance, contribute to long-term roadmaps, and mentor engineering staff.

Design, develop, deploy, and support production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize model performance, scalability, latency, throughput, hardware utilization, and cost. Architect multi-model orchestration pipelines, lead AI governance and technical design reviews, establish engineering standards, and mentor senior technical staff.

Leads an AI engineering team building scalable, responsible generative AI platform services, including foundation model training, LLM inference, similarity search, guardrails, evaluation, observability, and governance. Establishes technical strategy, optimizes production AI systems for cost and performance, manages cloud deployments, translates enterprise goals into roadmaps, and develops engineering talent.

Designs, develops, deploys, and supports foundational AI systems, including LLM inference, foundation model training, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimizes AI systems for cost, latency, throughput, scalability, and hardware utilization. Owns complex AI architecture, defines reliability objectives, leads technical reviews, ensures security and compliance, contributes to long-term technical roadmaps, and mentors senior and principal engineers.

Design, develop, deploy, and optimize foundational AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, and observability. Lead multi-model orchestration, cost-performance governance, technical standards, roadmap development, and design reviews. Mentor senior AI engineers while applying advanced optimization techniques to improve scalability, latency, throughput, hardware utilization, and inference costs.

Design, develop, deploy, and support foundational AI systems, including foundation-model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize distributed AI systems for cost, latency, throughput, scalability, and hardware utilization. Own complex architectures, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to long-term AI roadmaps, and mentor engineering teams.

Designs, develops, deploys, and supports scalable AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. The role optimizes model performance, GPU/TPU utilization, latency, throughput, and cost; owns complex AI architecture; defines reliability objectives; leads technical reviews; and mentors engineering teams.

Design, develop, deploy, and optimize foundational AI systems, including LLM inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture, cost-performance optimization, technical standards, and roadmap development for scalable production AI platforms. Partner with researchers, engineers, technical program managers, and product managers while mentoring senior technical staff and advancing responsible AI practices.

Build and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Design multi-model orchestration pipelines, improve model cost, latency, throughput, and scalability, establish AI governance standards, lead technical reviews, and mentor senior AI engineering staff. Collaborate with engineers, scientists, technical program managers, and product managers to deliver responsible AI capabilities.

Build and optimize foundational AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead multi-model orchestration, cost-performance optimization, technical standards, and design reviews for scalable production AI. Partner cross-functionally, contribute to long-term AI roadmaps, and mentor senior technical leaders while applying state-of-the-art research to responsible AI systems.

Design, develop, deploy, and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture and cost-performance governance for scalable AI platforms, establish engineering standards, contribute to technical roadmaps, and mentor senior AI engineers. Collaborate with scientists, engineers, technical program managers, and product managers to deliver responsible AI products.

Design, develop, deploy, and support production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI platforms for cost, latency, throughput, scalability, and hardware utilization. Lead architecture and governance reviews, shape long-term platform roadmaps, establish engineering standards, and mentor senior AI engineers across the organization.

Build and lead scalable generative AI platforms, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, and hardware utilization; architect multi-model orchestration pipelines; establish technical standards and governance; and mentor senior AI engineers while shaping the long-term platform roadmap.

Build and optimize foundational AI systems, including LLM training and inference, agentic workflows, vector search, guardrails, evaluation, and observability. Partner with engineering, research, product, and program teams to deliver scalable AI products. Lead model and infrastructure optimization for cost, latency, throughput, and hardware utilization; establish governance and engineering standards; contribute to technical roadmaps; and mentor senior AI leaders.

Develop and deploy foundational AI systems, including foundation model training, LLM inference, agent workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for scalability, cost, latency, throughput, and hardware utilization. Build training and deployment pipelines, improve datasets and evaluation methods, support responsible AI practices, and mentor junior engineers while contributing to long-term technical strategy.

Design, develop, deploy, and optimize large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, and multi-model orchestration. Lead cost-performance governance, technical design reviews, AI engineering standards, and long-term platform strategy. Apply state-of-the-art optimization techniques to improve model scalability, latency, throughput, hardware utilization, and cost. Mentor senior technical leaders and collaborate with engineers, scientists, product managers, and program managers.

Design, develop, deploy, and support large-scale AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI infrastructure for cost, latency, throughput, scalability, and hardware utilization. Lead architecture reviews, establish technical standards, contribute to foundational AI roadmaps, and mentor senior engineering leaders.