13 of 13 Remote Autonomous Agent Jobs

in Python, experienced in building multi-step intelligent systems, and comfortable working across UI, APIs, cloud AI platforms, and observability tools. Responsibilities Rapidly build and iterate on LLM- and agent-based prototypes for various use cases, including chatbots, copilots, and A2A task agents. Implement agentic workflows, multi-step reasoning pipelines, and memory management using frameworks such as LangChain, CrewAI … to implement applications that adhere to responsible AI guidelines. Optimize model performance for latency, throughput, and cost-efficiency. Implement short-term and long-term memory modules to support persistent agent behaviours. Use cloud platforms such as Amazon Bedrock, Google Vertex AI, and Azure AI Studio for model orchestration and deployment. Build and integrate UI prototypes using tools like React … in Python programming. Experience in building multi-step intelligent systems. Knowledge of machine learning and artificial intelligence. Familiarity with frameworks like LangChain and CrewAI. Additional Skills & Qualifications Experience with agent collaboration (A2A) or multi-agent task routing systems. Familiarity with MCP tools or advanced model configuration systems. Understanding of prompt injection prevention, ethical AI, and safety frameworks. Background More ❯

AI Engineer with a Google/GCP focus to join a forward-thinking AI engineering team pushing the boundaries of what's possible with large language models and autonomous agents. This is a fast-paced, hands-on opportunity for someone … excited by cutting-edge AI tools and frameworks, who thrives in an environment of experimentation, iteration, and deep technical problem-solving. Key Responsibilities: Rapidly design and develop LLM and agent-based prototypes across varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using … vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. Integrate semantic search strategies and embeddings to improve LLM More ❯

AI Engineer with a Google/GCP focus to join a forward-thinking AI engineering team pushing the boundaries of what's possible with large language models and autonomous agents. This is a fast-paced, hands-on opportunity for someone … excited by cutting-edge AI tools and frameworks, who thrives in an environment of experimentation, iteration, and deep technical problem-solving. Key Responsibilities: Rapidly design and develop LLM and agent-based prototypes across varied use cases. Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. Implement retrieval-augmented generation (RAG) pipelines using … vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. Fine-tune prompts to optimise performance, reliability, and alignment. Design and implement memory modules for short-term and long-term agent behaviours. Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. Integrate semantic search strategies and embeddings to improve LLM More ❯

AI Engineer with a Google/GCP focus to join a forward-thinking AI engineering team pushing the boundaries of what's possible with large language models and autonomous agents. This is a fast-paced, hands-on opportunity for someone … excited by cutting-edge AI tools and frameworks, who thrives in an environment of experimentation, iteration, and deep technical problem-solving. Key Responsibilities: • Rapidly design and develop LLM and agent-based prototypes across varied use cases. • Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. • Implement retrieval-augmented generation (RAG) pipelines using … vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. • Fine-tune prompts to optimise performance, reliability, and alignment. • Design and implement memory modules for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. • Integrate semantic search strategies and embeddings to improve LLM More ❯

AI Architect with a Google/GCP focus to join a forward-thinking AI engineering team pushing the boundaries of what's possible with large language models and autonomous agents. This is a fast-paced, hands-on opportunity for someone … excited by cutting-edge AI tools and frameworks, who thrives in an environment of experimentation, iteration, and deep technical problem-solving. Key Responsibilities: • Rapidly design and develop LLM and agent-based prototypes across varied use cases. • Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. • Implement retrieval-augmented generation (RAG) pipelines using … vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. • Fine-tune prompts to optimise performance, reliability, and alignment. • Design and implement memory modules for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. • Integrate semantic search strategies and embeddings to improve LLM More ❯

AI Architect with a Google/GCP focus to join a forward-thinking AI engineering team pushing the boundaries of what's possible with large language models and autonomous agents. This is a fast-paced, hands-on opportunity for someone … excited by cutting-edge AI tools and frameworks, who thrives in an environment of experimentation, iteration, and deep technical problem-solving. Key Responsibilities: • Rapidly design and develop LLM and agent-based prototypes across varied use cases. • Build agentic workflows and reasoning pipelines using frameworks such as LangChain, LangGraph, CrewAI, Autogen, and LangFlow. • Implement retrieval-augmented generation (RAG) pipelines using … vector databases like Pinecone, FAISS, Chroma, or PostgreSQL. • Fine-tune prompts to optimise performance, reliability, and alignment. • Design and implement memory modules for short-term and long-term agent behaviours. • Deploy models and orchestrate AI systems on cloud platforms such as AWS Bedrock, Google Vertex AI, and Azure AI Studio. • Integrate semantic search strategies and embeddings to improve LLM More ❯

Qualifications: Experience building and deploying Generative AI applications, e.g., LLM (Large Language Model) fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation) systems. Exposure to agentic AI systems (e.g., autonomous agents, tool usage frameworks, multi-step reasoning models). Able to implement large language models. Familiarity with MLOps (Machine Learning Operations) platforms: MLflow, Snowpark or ML Kubeflow and experience More ❯

design and delivery of agentic AI systems across financial and retail B2C enterprises. You’ll architect large-scale AI agents that operate autonomously within production environments, integrating LLMs, multi-agent workflows, cloud-native infrastructure and real-time API interfaces. Experience translating ML models into resilient cloud applications, optimizing for performance, observability and secure operations at scale. Core Responsibilities Architect … LLMs and tool-using AI components across enterprise cloud environments Design and implement modular, event-driven architectures (e.g., Lambda + SQS/SNS + Step Functions) to enable scalable agent workflows Develop and manage API layers (REST, GraphQL, WebSockets) to orchestrate intelligent interactions between agents, models and services Lead implementation of full-stack interfaces and services using Node.js, TypeScript … memory storage, vector search (e.g., Pinecone, Weaviate) and tool registries Enforce system-level requirements for security, compliance, observability and CI/CD Drive PoCs and reference architectures for multi-agent coordination , intelligent routing and goal-directed AI behavior Contribute to internal standards for scalable AI deployments, model governance, and fail-safe operations Must-Have Skills 5+ years in enterprise More ❯

design and delivery of agentic AI systems across financial and retail B2C enterprises. You’ll architect large-scale AI agents that operate autonomously within production environments, integrating LLMs, multi-agent workflows, cloud-native infrastructure and real-time API interfaces. Experience translating ML models into resilient cloud applications, optimizing for performance, observability and secure operations at scale. Core Responsibilities Architect … LLMs and tool-using AI components across enterprise cloud environments Design and implement modular, event-driven architectures (e.g., Lambda + SQS/SNS + Step Functions) to enable scalable agent workflows Develop and manage API layers (REST, GraphQL, WebSockets) to orchestrate intelligent interactions between agents, models and services Lead implementation of full-stack interfaces and services using Node.js, TypeScript … memory storage, vector search (e.g., Pinecone, Weaviate) and tool registries Enforce system-level requirements for security, compliance, observability and CI/CD Drive PoCs and reference architectures for multi-agent coordination , intelligent routing and goal-directed AI behavior Contribute to internal standards for scalable AI deployments, model governance, and fail-safe operations Must-Have Skills 5+ years in enterprise More ❯

are seeking a highly skilled AI Engineer to lead the development of advanced agentic workflows that transform how scientists interact with our platform. You will design and implement autonomous systems capable of navigating complex scientific tasks—such as retrieving scientific data and designing protein binders—using natural language interfaces. In this role, you will architect and deploy intelligent … with expertise in Python, API design, and distributed systems. Skilled in LLM orchestration, with hands-on experience using APIs (e.g. OpenAI, Anthropic) and frameworks like LangChain, LlamaIndex, or custom agent platforms. Proficient in intelligent information retrieval, including RAG systems, vector databases, and embedding models. Capable of architecting complex, multi-step workflows with tools such as Airflow, Prefect, or Temporal. … and data extraction from research papers. Familiarity with academic or pharmaceutical research workflows. Expertise in natural language processing, particularly for scientific texts and citation networks. Key Responsibilities Develop autonomous agents capable of executing complex scientific workflows through natural language. Architect end-to-end systems that integrate platform capabilities with decision-making for advanced scientific tasks. Build pipelines for More ❯

are seeking a highly skilled AI Engineer to lead the development of advanced agentic workflows that transform how scientists interact with our platform. You will design and implement autonomous systems capable of navigating complex scientific tasks—such as retrieving scientific data and designing protein binders—using natural language interfaces. In this role, you will architect and deploy intelligent … with expertise in Python, API design, and distributed systems. Skilled in LLM orchestration, with hands-on experience using APIs (e.g. OpenAI, Anthropic) and frameworks like LangChain, LlamaIndex, or custom agent platforms. Proficient in intelligent information retrieval, including RAG systems, vector databases, and embedding models. Capable of architecting complex, multi-step workflows with tools such as Airflow, Prefect, or Temporal. … and data extraction from research papers. Familiarity with academic or pharmaceutical research workflows. Expertise in natural language processing, particularly for scientific texts and citation networks. Key Responsibilities Develop autonomous agents capable of executing complex scientific workflows through natural language. Architect end-to-end systems that integrate platform capabilities with decision-making for advanced scientific tasks. Build pipelines for More ❯

units. This person will work closely with GTO's Enterprise Architect and Solution Architect in a "3-in-a-box" model to ensure alignment, scalability, and compliance across all agent-based initiatives. Key Responsibilities: Architectural Leadership: Lead the definition and evolution of the agentic architecture framework across RDS workflows. Collaborate with GTO's Enterprise Architect and Solution Architect to … ensure consistency, compliance, and alignment with enterprise standards. Ensure architectural decisions support scalability, security, maintainability, and performance of agent-based systems. Agent Development Oversight: Provide technical leadership and oversight in the development of agentic workflows across RDS squads. Guide engineering teams on best practices in building, testing, and deploying intelligent agents. Evaluate and recommend tools, frameworks, and platforms … for agent development. Cross-Functional Collaboration: Serve as the key liaison between RDS squads and GTO, translating squad-level requirements into enterprise architecture and tech stack decisions. Facilitate feedback loops from development teams back to GTO to influence strategic choices in infrastructure, tooling, and platform evolution. Ecosystem Integration: Assess the current RDS technology ecosystem to determine integration points, dependencies More ❯

the frontier of AI/ML research and application? This is your opportunity to steer innovation that matters—developing technology that underpins national security, space capability, and intelligent autonomous systems. We're looking for a Lead Technologist to help guide a technically diverse AI/ML team tackling real-world, mission-critical challenges across reinforcement learning, natural language … track record of leadership in R&D environments Demonstrated expertise in at least one of the following: AI/ML for imagery (incl. remote sensing) Reinforcement learning or autonomous agents NLP, LLMs, or knowledge graph technologies AI for RF/EW, radar, sonar, or acoustic domains Strong Python skills and familiarity with ML toolkits (e.g. PyTorch, TensorFlow, Scikit More ❯