126 to 150 of 253 Model Context Protocol Jobs

deliver outcomes and build long‐term technical trust. Our Tech Stack Typescript, NodeJS, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP Who you are Experience level: 8+ years in software engineering, systems integration, DevOps, or data engineering roles with meaningful production responsibility. People leadership: proven ability ...

interface between business outcomes and technical execution to mature how STOXX delivers index data to clients globally, including Web portals, APIs, bulk delivery mechanisms, MCP (AI‐enabling pipelines) and third‐party data marketplace integrations. The role owns the product vision, roadmap, and delivery outcomes for index data distribution and must ...

/UDP , packet and latency path analysis, dedicated network infrastructure, and kernel bypass techniques ( DPDK ) Familiarity with agentic engineering tools and concepts: LLMs , MCP APIs , AI‐First IDEs (e.g. Cursor, Claude Code), harness engineering , and workflow automation Ability to make sound architectural decisions, articulate trade‐offs clearly, and guide implementation ...

/ML solutions, ensuring security, scalability, and observability. Implementing CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance. Establishing robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations. Contributing to reusable … batch and real‐time). Familiarity with RAG architectures, prompt engineering, guardrails and evaluation techniques. Previous experience developing agentic capabilities, such as agent skills, MCP servers, tool usage. Strong grasp of security, privacy and governance principles (IAM, secrets, PII handling). Effective communication skills and ability to work with both ...

/ML solutions, ensuring security, scalability, and observability. Implementing CI/CD for ML services, writing infrastructure as code, and monitoring for model/data drift and performance. Establishing robust guardrails for safe AI usage, including prompt security, practical evaluation frameworks, and compliance with privacy regulations. Contributing to reusable … batch and real-time). Familiarity with RAG architectures, prompt engineering, guardrails and evaluation techniques. Previous experience developing agentive capabilities, such as agent skills, MCP servers, tool usage. Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling). Effective communication skills and ability to work with both ...

should have: Good understanding of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), and modern AI frameworks such as LangChain, LangGraph, MCP, with experience developing AI-powered applications. Experience working with vector databases, semantic search, and retrieval optimisation techniques, along with an understanding of context management. Experience ...

Azure. Experience with Python/Fast API for backend development. Experience using AI-assisted development tools. Awareness or exposure to Model Context Protocol. Experience working with Figma or collaborating from design files. Exposure to AI agents or agent-based workflows. Benefits: Competitive salary based on experience. Opportunity ...

Group in London is seeking a Senior ML Engineer to advance safe, scalable agentic AI capabilities across the enterprise. You will design and operate MCP-based platforms and collaborate with product teams to deliver reliable AI tooling. The role requires strong Python, expertise with LLM frameworks, FastAPI, and Kubernetes, plus ...

Kubernetes, Docker, Linux, Kafka, RabbitMQ, or git. Using AI coding assistants to accelerate development while owning the outcome. Exposure to agentic frameworks or MCP server development. Knowledge of financial concepts, exchange trading, or physical energy trading. #J-18808-Ljbffr ...

record of production delivery Able to communicate ideas clearly and build strong relationships globally within the front office Previous experience of agentic design (harnesses), MCP servers, and related AI/ML python libraries Strong analytical, problem-solving, and architectural design skills, with an ability to operate effectively in a front ...

oriented programming language (e.g., JavaScript/TypeScript, Python, Java, C#, etc.). AI & Next-Gen Tech: * Hands-on experience with GenAI (e.g., Playwright with MCP). Required experience with AI-assisted coding tools (e.g., GitHub Copilot, Claude). Knowledge of LangChain , LangGraph , or cloud environments is highly desirable (a plus ...

shipped recently Cut ~$50k/year off our Elasticsearch bill by migrating compute to more efficient chips. (Apr 2026) Built the foundation for our MCP server platform : leveraging and contributing to open-source tooling to give the whole company extensible, production-grade AI integrations. (2025–2026) Rebuilt production from scratch ...

architects. Proven ability to manage multiple workstreams, prioritize trade-offs, and drive work through to production with high quality. Hands-on experience integrating with MCP - style patterns for connecting agents to external systems. Prior involvement in early adopter programs for new AI or platform capabilities. Extensive knowledge of web service ...

frameworks using network documentation, alarms, topology, inventory, KPIs, trouble tickets, procedures, configuration data, and operational knowledge. Develop multi-agent workflows using LangChain, LangGraph, MCP, or similar frameworks. Implement vector search, semantic retrieval, graph-enhanced retrieval, and hybrid search patterns. Develop AI agents for fault diagnosis, root-cause analysis, KPI analysis … systems. Strong Python programming skills. Experience with ML fundamentals, deep learning concepts, embeddings, transformers, and LLM architectures. Experience using LangChain, LangGraph, LlamaIndex, AutoGen, MCP, or similar AI frameworks. Experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, ChromaDB, or equivalent. Experience with graph databases, knowledge graphs, or Graph APIs. ...

others. Agentic AI & LLM Engineering Design and build production‐grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. Strong opinions on secure, resilient enterprise deployment of LLM‐powered systems; current knowledge of the latest model capabilities … product stacks. Machine Learning Engineering End‐to‐end ML lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery ...

individual-contributor role for engineers who live at the current edge of AI development and work fluently with Claude Code, Cursor, agents, eval harnesses, MCP, and modern TypeScript and Python. What You’ll Do Problem/Opportunity Discovery Sit with a business or clinical leader and reframe an idea … your own orchestration layer. Integrate frontier and self-hosted LLMs (Claude, GPT, Gemini, open-weight models) with tools, data, and external systems through MCP and custom connectors. Apply RAG techniques where they actually help: vector databases (Pinecone, Chroma, Weaviate, pgvector), hybrid retrieval with Elasticsearch or Solr, and BM25 + similarity ...

client delivery teams to design, build, and operate multi-agent AI systems on AWS. You'll own end-to-end implementations using Amazon Bedrock, MCP servers, and RAG pipelines, while ensuring observability, scalability, and secure integration with client applications. Hybrid and remote options offered, with offices in multiple cities. #J ...

agents across the business. You will own delivery, scale the function, and define its future. You\'ll work with Claude, Claude Code, MCP, LangChain to implement multi-agent systems, RAG pipelines, and tooling. This is a hands-on leadership role with three engineers initially. The role is fully remote within ...

tasks (containers, cloud configuration) — at Encore, engineers regularly jump between the two Experience working with AI-assisted coding tools, such as Claude Code Skills, MCP servers and Routines. A product and commercial mindset: the ability to weigh technical work against business impact, prioritise ruthlessly, and know what ...

Senior Lead AI Engineer (SDK's: Gen AI Evaluation and MCP) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments … change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source ...

Senior Lead AI Engineer (SDK's: Gen AI Evaluation and MCP) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments … change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source ...

others: Agentic AI & LLM Engineering Design and build production-grade agentic systems using major LLM SDKs and agent frameworks; deep knowledge of RAG, MCP servers and prompt engineering at scale. Strong opinions on secure, resilient enterprise deployment of LLM-powered systems; current knowledge of the latest model capabilities … product stacks. Machine Learning Engineering End-to-end ML lifecycleexpertise: feature engineering, model training,evaluationand production deployment, includingMLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit-learn,PyTorch,XGBoost) and cloud-native ML services (SageMaker, Azure ML, Vertex AI). Platform & Cloud Engineering Architecture and delivery ...

microservices for AI/ML solutions, ensuring security, scalability, and observability. Implementing CI/CD for MLservices,writinginfrastructure as code, and monitoring for model/data drift and performance. Establishingrobustguardrails for safe AI usage, including prompt security,practicalevaluation frameworks, and compliance with privacy regulations. Contributing to reusable components, documentation … operating MLsystemsin production (batch and real-time). Familiarity with RAG architectures, prompt engineering,guardrailsand evaluation techniques. Previousexperience developing agentic capabilities,such asagentskills, MCP servers,tool usage. Strong grasp of security, privacy, and governance principles (IAM, secrets, PII handling). Effectivecommunication skills and ability to work withboth technical andnon-technicalstakeholders. ...

systems: Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance, and least-privilege access. Productionize LLMs: Build evaluation framework for open-source and foundational LLMs; implement retrieval pipelines, prompt … fallbacks, circuit breakers, and rollback strategies; instrument continuous evaluations for usefulness, correctness, and risk. Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool-calls to meet stringent SLOs under real-world load. Build ...

intelligent systems using Azure OpenAI and other cloud-native AI tools. Apply advanced AI architecture patterns such as Retrieval-Augmented Generation (RAG), Agentic RAG, MCP, Function Calling, and A2A to practical enterprise use cases. Engineer robust pipelines for prompt design, context handling, embeddings, chunking strategies, and real-time data … Experience with AI/ML and agentic application frameworks such as LangChain, LangGraph, Pydantic Proficiency in advanced AI architecture patterns, including RAG, Agentic RAG, MCP, Function Calling, and A2A, especially in an Azure environment Good understanding of GPT token usage, latency analytics, and budget guardrails. Sound understanding of AI guardrails ...