Design and develop production-grade AI and NLP solutions to automate complex regulatory compliance tasks. Establish ML infrastructure and monitoring systems to ensure scalability, robustness, and ethical explainability.
Remote AI Engineer Jobs (2,201)
Search = AI Engineer
Design, build, and deploy complex generative AI solutions using RAG and multi-agent systems from prototype to production. Collaborate with cross-functional teams to deliver scalable systems while mentoring junior engineers and championing engineering best practices.
Design and develop advanced agentic AI solutions capable of autonomous planning, reasoning, and task execution. Integrate RAG pipelines and multi-agent communication protocols to deliver robust end-to-end AI solutions for the financial sector.
Design and develop high-quality, AI-native DevOps infrastructure and intelligent services to power the platform's growth engine. Collaborate with product teams to translate customer needs into scalable technical solutions while maintaining high code quality and CI/CD hygiene.
Senior Software Engineer — AI Evaluation & Benchmarks (Python)
G2i Inc.
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Full Time
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3 Weeks Ago
G2i Inc.
Design and build coding benchmarks and evaluation pipelines to test frontier AI models on real-world software engineering tasks. Analyze model-generated code for correctness and reliability to improve the training of next-generation models.
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Lead the design and development of enterprise-grade AI solutions and MCP servers on AWS. You will architect scalable AI infrastructure, automate LLM tool validation, and implement secure authentication flows.
Databricks Senior Data & AI Engineer
V2 Strategic Advisors
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Full Time
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3 Weeks Ago
V2 Strategic Advisors
Design and implement production-grade Lakehouse solutions using medallion architecture and scalable data pipelines. Build AI-powered applications and RAG pipelines while serving as a technical advisor for client engagements.
Lead technical enablement for AI adoption by building practical automations and integrating AI tools with internal enterprise systems. Own the technical foundations for AI enablement, including MCP connectivity, operational standards, and security governance.
Design and ship AI-enabled workflows to automate sales processes and improve decision-making across the GTM stack. Build reusable patterns and integrate systems like Salesforce and Slack to reduce manual work for reps and managers.
Lead the design, development, and deployment of scalable machine learning infrastructure and models on AWS to enhance a financial platform. Collaborate with product teams to build AI-driven features for personalized recommendations, fraud detection, and credit risk assessment.
Design, build, and scale enterprise-grade AI agents using Microsoft Copilot Studio and agentic orchestration. Integrate these agents with enterprise systems via Power Automate and APIs to drive business value.
Python Engineer – AI Agents & LLM Systems
INNOCV Solutions S.L.U.
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Full Time
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3 Weeks Ago
INNOCV Solutions S.L.U.
Design and implement AI solutions using RAG and autonomous agent networks to solve complex business problems. Manage data ingestion pipelines and deploy models using MLOps practices and serverless architectures.
Design, implement, and deploy performant backend capabilities and sophisticated Agentic AI systems. Lead technical delivery from design to deployment while improving system observability, scaling, and automation.
Design and deploy AI-driven applications and agentic systems using LLMs and reinforcement learning to enhance enterprise automation. Collaborate with cross-functional teams to integrate AI capabilities into infrastructure and develop scalable APIs for model orchestration.
Develop specialized AI systems for structured content generation, editing, and optimization within creative workflows. Design fine-tuning strategies and build automated pipelines for data collection and model evaluation.
AI Engineer ReactJS Foundation - REMOTE
NTT DATA Services
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Full Time
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3 Weeks Ago
NTT DATA Services
Design, develop, and implement AI-driven solutions and agents from scratch based on product requirements. Collaborate with stakeholders to align AI systems with business strategy and perform ongoing maintenance through conversation review and metric evaluation.
Design and develop a next-generation Agentic AI Platform to support autonomous workflows and complex financial operations. Lead the architecture of scalable backend services, AI agents, and integration frameworks to empower internal feature development teams.
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Design, implement, and deploy end-to-end production AI/ML systems, including data pipelines and training workflows. Collaborate with cross-functional teams to integrate AI agents into enterprise operations and maintain system reliability and scalability.
Design, implement, and deploy end-to-end production AI/ML systems, including data pipelines and training workflows. Collaborate with cross-functional teams to integrate AI agents into enterprise operations and maintain system reliability.
The role involves designing and implementing AI-powered software solutions and scalable backend services to automate business processes. You will be responsible for the technical lifecycle of AI projects, from architecture design to productive operation and client guidance.
Design and build internal AI-powered platform tools to enable engineering teams to execute functional and non-functional testing. Focus on creating scalable infrastructure and AI agent orchestration to identify performance bottlenecks and improve development efficiency.
Senior Python Engineer – AI Agents & LLM Systems
INNOCV Solutions S.L.U.
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Full Time
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3 Weeks Ago
INNOCV Solutions S.L.U.
Design and implement AI solutions using RAG and autonomous agent networks to solve complex business problems. Manage data ingestion pipelines, serverless architectures, and MLOps practices to automate the deployment of AI models.
Rapidly transform rough ideas and sketches into clickable iOS prototypes and native surfaces like Live Activities and Dynamic Island. Collaborate directly with founders and designers to iterate on AI-powered features and orchestrate AI agents for code generation and testing.
Develop AI pipelines and lead feature development to bring a product to market. Responsibilities include maintaining the codebase, building eval pipelines, and managing infrastructure stability and scalability.
Develop AI-assisted tooling and agents to improve engineering productivity, CI/CD pipelines, and operational workflows. Design and maintain production-grade AI services, including RAG systems and internal engineering copilots, to reduce manual overhead.
Design and scale asynchronous APIs and multi-agent AI workflows using Python and Semantic Kernel. Implement RAG systems and integrate various LLM providers while maintaining robust CI/CD pipelines and observability.
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Lead the AI Engineering Lab by designing and deploying multi-agent architectures and autonomous agents to optimize engineering workflows. Drive technical excellence through high-standard code implementation, mentoring peers, and managing the full development lifecycle of AI tools.
JD: Software Engineer (AI / Data Platform) – Remote
RedChip Companies
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Full Time
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3 Weeks Ago
RedChip Companies
Build and scale an AI-powered financial research platform by designing data pipelines for SEC filings and market data. Develop backend APIs and semantic search systems to power AI workflows and internal analytics dashboards.
![Smart Working Solutions is hiring for remote Senior AI Engineer (Remote, Full-Time) [AS237]](/assets/08150176-369d-44db-a4a7-778571334971.png){kind=small}
Senior AI Engineer (Remote, Full-Time) [AS237]
Smart Working Solutions
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Full Time
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3 Weeks Ago
Smart Working Solutions
Design and implement an end-to-end AI-powered tender response platform using AWS-native technologies and Terraform. Develop scalable backend services, AI retrieval workflows, and orchestrate processes using AWS Step Functions.
Implement and deploy end-to-end enterprise AI solutions and RAG pipelines on the Azure stack. Establish AI guardrails, observability, and CI/CD pipelines to ensure secure and compliant production-ready AI services.
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