Design and develop advanced AI solutions based on LLMs, including synthetic AI personas and insight generation tools. Build scalable backend services, data pipelines, and integrations to support decision-making in the pharmaceutical sector.
Remote AI Engineer Jobs (2,817)
Search = AI Engineer
You will act as the first dedicated AI engineer to identify and solve high-leverage workflow problems across all company departments. This involves scoping, building, securing, and maintaining custom AI tools and integrations to improve operational efficiency.
You will design, build, and optimize complex UI components for a modern integration platform using advanced web technologies. You will also collaborate with product and design teams to iterate on features and resolve performance issues.
You will productionize and scale AI agent swarms by building robust evaluation harnesses, observability tools, and data pipelines. Your role involves ensuring agent reliability, implementing human-in-the-loop review surfaces, and expanding agent capabilities to operate across real-world web interfaces.
You will build and maintain agentic features and AI-powered products within a cross-functional Data Science & AI team. This role involves leading technical discussions, shaping architectural foundations, and writing clean, maintainable code for a leading European neo-broker.
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Support the delivery of agentic AI and AWS modernization projects by building and testing components under the guidance of Forward-Deployed Engineers. Assist in converting existing functionality into callable agent tools and document technical decisions to ensure traceability.
Embed within functional departments to scope, design, and build full-stack custom applications using modern AI tools. Own the end-to-end delivery process, including architecture, testing, deployment, and stakeholder training.
Embed within functional departments to discover pain points and design custom full-stack applications using modern AI tools. Own the end-to-end delivery of these applications, including architecture, testing, deployment, and stakeholder training.
The Principal Software Engineer will drive cross-team architectural decisions for the AI SIEM platform, ensuring seamless integration between data ingest, analyst workflows, and detection engines. They will mentor senior engineers and establish technical standards to maintain system interoperability and performance at scale.
Design, develop, and implement enterprise-grade solutions using Generative AI, Machine Learning, and Intelligent Automation on Microsoft Azure. Manage data pipelines, ensure secure AI governance, and oversee the deployment and operational performance of AI models in production.
You will design, build, and deploy production-grade AI-powered services and microservices while embedding with customer teams to solve real-world business problems. This involves managing the full lifecycle of AI features, from discovery and implementation to evaluation and post-launch support.
2013 Sr QA Automation Engineer - AI First
In All Media Inc
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Full Time
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1 Week Ago
In All Media Inc
The Senior QA Automation Engineer will design and enforce a robust automated testing strategy for distributed systems, Python microservices, and agentic AI workflows. They will also integrate test suites into CI/CD pipelines as quality gates and perform root-cause analysis to resolve test flakiness.
You will design and build complex backend AI modules, including agentic workflows and RAG pipelines, while ensuring production-grade performance and scalability. You will also own the end-to-end delivery of AI components and contribute to internal tooling to streamline future client engagements.
You will design and build modern, responsive web applications to power AI Receptionist experiences for enterprise customers. This involves collaborating with cross-functional teams to integrate frontend applications with backend services and AI-powered capabilities.
The specialist will architect, develop, and operationalize next-generation agentic systems using advanced LLMs and Model Context Protocol frameworks. They will provide technical leadership to build intelligent, multi-step, tool-using agents that autonomously reason and execute complex workflows.
The Edge AI Engineer will design, optimize, and deploy machine learning models for resource-constrained edge devices. This role involves performing hardware-aware optimizations and ensuring reliable AI deployment outside of data centers.
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The AI Risk Engineer will design and implement security controls for AI and LLM-based applications while building threat models to mitigate risks like prompt injection and model abuse. They will also collaborate with security and compliance teams to conduct AI security assessments and drive remediation efforts.
Design and implement production-grade multi-agent AI systems using frameworks like Semantic Kernel and AutoGen. Integrate AI solutions with Microsoft Fabric, enterprise data sources, and business platforms like DealCloud.
You will design and deliver production-grade Generative AI systems on AWS, including RAG pipelines and agent-based workflows. The role involves collaborating with client teams to turn POCs into scalable, reliable systems while managing the full project lifecycle.
AI / ML Engineer (Generative AI Engineer)
TECDATA ENGINEERING
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Full Time
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1 Week Ago
TECDATA ENGINEERING
Collaborate on the design and implementation of innovative AI-based solutions to meet project requirements. Optimize existing machine learning models for performance and scalability while contributing to technical documentation.
The Senior AI Engineer leads the design, development, and operationalization of AI and intelligent automation solutions using Microsoft's end-to-end stack. They are responsible for setting technical direction, mentoring team members, and ensuring solutions are deployed securely and effectively into production.
Design and develop production-grade AI and NLP solutions to automate complex regulatory compliance tasks. Lead the transition of ML models from proof-of-concept to scalable production infrastructure while ensuring ethical standards and explainability.
Build and prototype full-stack AI applications and agentic systems to solve real-world enterprise use cases for strategic customers. Partner with customer leaders to shape AI roadmaps and codify successful patterns into repeatable reference architectures.
Design and implement integration and automation systems that orchestrate connectors and manage data streams for AI use cases. Develop backend solutions using Python and LangGraph to integrate LLM-driven processes into productive workflows.
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AI Engineer (Search & Matching) - fully remote within Germany (m/f/d) Remote
JobLeads Careers
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Full Time
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1 Week Ago
JobLeads Careers
Design and improve large-scale retrieval systems, including semantic search and LLM-driven query understanding for job matching. Own the scientific evaluation process by curating benchmarks and conducting rigorous A/B testing to optimize search quality and latency.
Establish the technical direction and architecture for a clinical AI data platform, ensuring secure and compliant PHI data pipelines on AWS. Lead the development of data quality frameworks, MLOps infrastructure, and clinical knowledge graphs while mentoring senior engineering staff.
Build, scale, and maintain biosecurity evaluations to measure dual-use biology capabilities in frontier AI systems. Develop internal tools and cloud infrastructure to enable large-scale capability assessments and public trend analysis.
Build and iterate an AI-native growth engine using agent orchestrations and automated workflows to power distribution decisions. Develop integrations between AI reasoning layers, execution platforms, and data infrastructure to automate growth levers like paid media and lifecycle messaging.
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