Build and operate production AI pipelines and Airflow-based orchestration for clinical workflows. Develop observability and evaluation infrastructure to ensure the quality and reliability of LLM outputs in healthcare applications.
Remote AI Engineer Jobs (2,146)
Search = AI Engineer
Develop the core language learning platform using agentic AI workflows and production-grade AI-assisted processes. Act as a technical leader to raise the AI fluency of the engineering organization through mentoring and sharing playbooks.
Build and maintain AI tooling, including MCP and agent skills, to enhance the Supabase developer experience. Drive an eval-first approach to improve AI reliability and integrate AI capabilities into product surfaces like the dashboard assistant.
AI Automation Engineer – Agentic AI (Python)
Precisely International Jobs
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Full Time
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2 Weeks Ago
Precisely International Jobs
Design and implement AI-driven automation pipelines and agents to streamline documentation and localization workflows. Integrate various content systems using APIs and MCPs to reduce manual effort and improve scalability.
Lead the architecture and evolution of backend and applied AI systems to deliver personalized shopper experiences. Design end-to-end AI services, create reusable building blocks for product teams, and provide technical leadership across multiple organizations.
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Lead the end-to-end delivery of scalable backend services and applied AI systems to power personalized shopper experiences. Design and maintain data pipelines and integrate LLM capabilities into production-hardened systems with automated evaluation frameworks.
Design, build, and operate the production AI runtime platform to power AI-first features. Ensure AI systems are scalable, secure, and reliable through observability, monitoring, and optimized deployment pipelines.
Design, build, and operate the production AI runtime platform to power AI-first features. Ensure the system is scalable, secure, and reliable through observability, monitoring, and optimized performance.
Principal AI Data Engineer
Thermo Fisher Scientific
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Full Time
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2 Weeks Ago
Thermo Fisher Scientific
Design and build data product solutions that enable AI agents to reliably access and reason over enterprise and clinical data. Focus on transforming raw data into use-case-ready products using Snowflake, SQL, and modern AI tooling.
Drive an AI-first engineering culture by creating internal playbooks, reusable patterns, and managing AI costs and guardrails. Build and document LLM pipelines and integrate AI tools into the developer lifecycle using AWS infrastructure and CI/CD.
Embed within business functions to identify and build production-ready agentic workflows using the AI Native Platform. Act as a bridge between non-technical departments and the platform team to shape the evolution of the End User Workbench.
Develop and maintain GenAI/LLM data pipelines and agentic frameworks using Python. Collaborate with software and ML engineers to implement analytical models into production for commercial and internal use.
Define and drive an AI-based QA strategy while establishing testing processes and methodologies from scratch. Ensure codebase security through a mix of manual exploratory testing and automation across backend, frontend, and infrastructure.
Lead the architecture, deployment, and governance of enterprise-grade autonomous AI agents using AWS Bedrock. You will transition experimental AI prototypes into scalable production systems while ensuring strict security and compliance standards.
Build and deploy a comprehensive business automation system integrating customer communication, lead management, finance, and internal operations. The role involves setting up infrastructure on VPS and developing approximately 35 workflows across five operational domains.
Serve as the senior technical escalation point for identity, SaaS, and MDM issues while managing the company's broader SaaS estate. Design and govern AI-powered tools and workflows to accelerate IT operations and infrastructure scaling.
Build and maintain the technical capability layer for company-wide AI productivity, focusing on agentic AI infrastructure and self-service tooling. Own the connector layer, execution environments, and AI governance to ensure safe and scalable deployment of AI workflows.
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AI Infrastructure Engineer
General Dynamics Mission Systems, Inc
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Full Time
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3 Weeks Ago
General Dynamics Mission Systems, Inc
Design and implement AI-powered infrastructure for automated deployment, self-healing systems, and intelligent data management. Build the CI/CD backbone and observability frameworks to ensure high reliability and scalability for strategic software initiatives.
AI Software Engineer - Mid Level
General Dynamics Mission Systems, Inc
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Full Time
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3 Weeks Ago
General Dynamics Mission Systems, Inc
Develop and maintain LLM API integrations and RAG pipelines while building backend APIs in Python. The role also involves conducting code reviews, mentoring junior engineers, and integrating enterprise systems like SharePoint and GitLab.
Full Stack Software Engineer - Audio AI
The Audio Programmer
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Full Time
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3 Weeks Ago
The Audio Programmer
The engineer will be part of the core R&D team responsible for building, testing, and shipping AI-powered features. The goal is to accelerate the integration of AI into music creation tools.
Lead end-to-end technical deployments of GPU infrastructure for neocloud and AI Factory customers from bare metal to production. Collaborate with Engineering and Product teams to create reusable deployment playbooks and provide field feedback for the product roadmap.
Own the technical delivery and stabilization of agentic AI solutions from design through production rollout in customer environments. Translate complex business problems into feasible AI workflows and serve as the primary technical point of contact for stakeholders.
Senior Software Engineer - SAM AI
SuiteSpot Technology
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Full Time
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3 Weeks Ago
SuiteSpot Technology
Build and scale the SAM AI agent across the full stack, focusing on voice and chat capabilities for resident maintenance. Own the end-to-end lifecycle from technical design and prompt iteration to production reliability and observability.
Act as a trusted technical advisor to customers by providing guidance on GenAI and ML best practices and delivering product demos. Partner with product and engineering teams to drive the roadmap and identify expansion opportunities within existing accounts.
Software Engineer Specialist – AI Tools Team
DLB Associates
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Full Time
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3 Weeks Ago
DLB Associates
Design, develop, and maintain AI-focused software tools and services using agentic AI platforms and Azure integrations. Collaborate with engineering teams to implement intelligent assistants and optimize workflows through AI/ML techniques.
Design and operationalize a scalable AI platform and service layer to support enterprise systems and customer-facing digital experiences. Collaborate with cross-functional teams to integrate AI capabilities like RAG pipelines and intelligent workflows into SaaS applications.
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Lead the design, deployment, and maintenance of AI systems while owning the product roadmap and high-level architecture. Bridge the gap between data science and product by translating complex problems into holistic AI solutions and managing cross-functional collaboration.
Architect and build scalable data infrastructure to power agentic AI systems, including LLM-based agents and multi-agent workflows. Design robust batch and real-time pipelines for embeddings, RAG systems, and agent memory frameworks.
Build and ship end-to-end AI-powered features, including backend logic, AI integration, and frontend experiences. Design APIs and services to connect AI systems with the product while optimizing for performance and cost.
Define success criteria and evaluation frameworks for AI-driven features to measure accuracy, consistency, and hallucination rates. Design and execute testing strategies, including exploratory and adversarial testing, to ensure the quality of intelligent tools.
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