Top Remote Artificial Intelligence Engineer Jobs in Boston, MA

Build and operate Coinbase's LLM and agent platform: design the LLM gateway, agent runtime, knowledge bases, AI spend governance, observability/eval tooling, and ship production agents while partnering cross-functionally to ensure secure, cost-effective, and responsible generative AI at scale.

The AI Automation Lead will architect and deliver multi-agent AI workflows, develop full-stack applications, and lead technical decisions across engineering teams.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Design and build LLM-powered agents for hardware product development. Responsibilities include ensuring effective coordination among engineering disciplines and integrating AI systems with existing tools.

Design, build, deploy, and maintain scalable, resilient backend services for a Voice AI platform. Lead cross-cutting projects, make architectural decisions, integrate AI platforms, implement observability and evaluation frameworks, and mentor engineers.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

As a Senior AI/Data Engineer, you will design and maintain scalable data and AI infrastructures, partnering with cross-functional teams to deliver reliable data systems and support AI-driven business capabilities.

Act as the technical presales lead for AI agent and cloud identity security across North America: scope engagements, design and run POCs and architectures across AWS/Azure/GCP, secure non-human and machine identities, create repeatable technical assets, and partner with account teams to close deals.

Client-facing AI engineer who develops and deploys generative AI/LLM solutions, collaborates with data scientists and engineers, leads cross-functional projects, and delivers technical solutions and presentations to clients.

Lead architect for patient data infrastructure, oversee AI-native workflows, ensure security compliance, and establish engineering culture in a founding role.

Develop AI solutions for marketing teams, integrating AI agents and workflows while coaching teams for self-sufficiency in AI use.

As a Senior AI Engineer at Knotch, you will develop AI agents for workflow automation, design backend and frontend services, and collaborate with teams to integrate AI into products. Your role includes optimizing systems for performance and ensuring agent safety and governance.

Lead architecture and delivery of agentic AI infrastructure: multi-agent orchestration, real-time conversational reasoning, retrieval/memory systems, LLM optimization, safety/observability, and secure tool integration. Mentor senior engineers and collaborate cross-functionally to build production-grade autonomous agents for enterprise workflows.

As a Lead Data Engineer, you'll design and implement AI-powered data systems, focusing on natural language queries and scalable frameworks. Collaborate with teams to optimize data access and enhance reporting tools.

As a Lead Software Engineer, you'll design and develop GenAI platforms, integrate LLMs, mentor engineers, and solve technical challenges for scalable solutions.

The role involves developing AI-powered features, including agent capabilities, ensuring their reliability and scalability, and collaborating with cross-functional teams. Candidates should have strong hands-on experience with LLMs and Python in production environments.

The Full Stack AI Engineer will develop and maintain AI agents, build clinician-facing products using React and Python frameworks, and manage data infrastructure to support clinical workflows.

Design and build autonomous, enterprise-grounded AI agents and workflows using the Elastic Stack, RAG, and LLMs. Integrate models with internal APIs and SaaS, manage deployment and scaling on cloud/Kubernetes, ensure security/compliance, document systems, and provide technical leadership for agent lifecycle and performance optimization.

The Senior AI Engineer designs and deploys AI agents and workflows, collaborating across teams to deliver reliable AI solutions that drive business outcomes.

The Senior AI Developer will build and maintain production-grade AI solutions, manage data pipelines, and collaborate on technical standards within the AI Operating Group.

The AI Engineer will design backend systems for workflows, optimize multi-agent pipelines, develop knowledge retrieval systems, and collaborate to integrate workflows using LLMs and traditional systems.

Maintain and expand the companys foundational AI platform codebase; support project teams to increase reuse (50-70%); fold successful project work back into the platform; address bugs and performance issues; create training, documentation, and onboarding; provide pairing and code reviews; and collaborate with sales and delivery teams on platform capabilities and project requirements.

Lead client-facing AI engineering engagements: build and deploy production LLM systems using RAG, vector DBs, and agent frameworks; handle cloud deployments, CI/CD, and reliability; debug enterprise issues (auth, networking, data); embed with client teams and document solutions for reuse.

Lead and deliver an enterprise AI platform and agent factory: design architecture, build cost-effective model infrastructure, harden security/SSO/IAM, enable developer adoption, and build agent workflows across the PDLC (ideation, development, deployment). Mentor engineers, steer delivery partners, and remain hands-on implementing agents, RAG pipelines, integrations, and observability to drive measurable productivity gains.

Build and deploy production AI capabilities for mental healthcare: full‑stack development, agentic systems, RAG and retrieval pipelines, evaluation frameworks, safety guardrails, observability, CI/CD, and cross‑functional collaboration to ensure safe, reliable AI in clinical workflows.