126 to 150 of 197 Model Context Protocol Jobs

looking for: Strong Solutions Architecture experience across cloud, integration and APIs Proven experience designing Generative AI, LLM and agentic AI solutions Knowledge of MCP, AI agent frameworks and tool integration Experience with AI governance, security and evaluation Excellent stakeholder engagement and technical leadership skills A fantastic opportunity to shape ...

ethical useNice to have: strong knowledge of AI/ML techniques with experience delivering related work into production previous experience of agentic design (harnesses), MCP servers, and related AI/ML python libraries strong understanding of data fundamentals and their python implementations (numpy, polars, scipy)About usUBS is a leading ...

solid grasp of statistics, experimentation and feature engineeringExperience with modern ML infrastructure on a major cloud platform, ideally AWS, covering distributed data processing, orchestration, model management and infrastructure as codeHands-on experience shipping agentic or LLM-based systems, including agent orchestration frameworks, tool use, RAG, and fine-tuning where … Terraform, GitHub Actions for CI/CDModels: foundation models served through Amazon BedrockAgents: LangGraph for orchestration, deployed and run on Amazon Bedrock AgentCore, with MCP for tool integrationEvaluation: Braintrust for evals, tracing and monitoring agent quality in productionMore information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work ...

agent-to-agent communication. Production experience with agent frameworks such as LangGraph, Microsoft Foundry, AWS Bedrock, CrewAI, AutoGen, or comparable orchestration tooling, plus MCP or similar protocols. Strong grounding in evaluation, observability and reliability for AI systems: eval suites, tracing, guardrails, monitoring and incident response for agentic workloads. Hands … experience with the Claude API, Claude Code, MCP, GitHub's AI tooling, or equivalent leading AI platforms and tooling, in production. A degree in a related field, or equivalent practical experience. What Version 1 gives you A role built around the craft, in front of the customer. This track exists ...

with experience developing and deploying solutions using LLMs, RAG architectures, and modern AI frameworks and protocols (Strands, FastMCP, LangChain, LlamaIndex, Hugging Face, A2A, MCP). Ability to translate multi-layered business problems into technical solutions with experience working directly with business stakeholders to understand requirements and deliver production systems. Experience … Python, cloud platforms (AWS/Azure), APIs, and full-stack development to rapidly prototype and productionise AI applications. Experience with MLOps practices including model deployment, monitoring, evaluation, and CI/CD pipelines with delivering AI solutions from concept to production. Some other highly valued skills may include: Excellent communication ...

cases and operational requirements Produce lightweight technical documentation, diagrams and decision records Quality, reliability and AI operations Implement evaluation frameworks and safety checks across model and agent behaviour Build monitoring, logging, tracing and incident-handling patterns Apply governance, risk and compliance principles to AI deployments Support release cycles, environments … data engineering Strong hands-on experience with LLMs, embeddings, RAG, retrieval stacks and vector stores Practical experience building multi-agent systems, agent orchestration or MCP-style tool patterns Strong Python, with a track record of production-grade workflows Experience with at least one cloud AI ecosystem: Azure OpenAI, Google Vertex ...

Google AI surfaces and the enterprise commerce stack - OMS, PIM, DAM, CRM, payments, and fulfilment — via APIs, event-driven patterns, and emerging agentic protocols (MCP, A2A, ACP).Leading GEO/AEO and AI-native discoverability design — structuring and exposing product content so brands remain visible, accurate, and preferred across … composable/MACH-aligned stack - and a solid understanding of how these integrate with surrounding enterprise systems. Familiarity with emerging agentic commerce protocols - MCP, A2A, or ACP - and how they connect AI agents to commerce systems and product data. Working knowledge of cloud-native services and CI/CD-based ...

balance model performance, reliability, security and operating costs in production systems Desirable skills include: Qdrant, Weaviate or pgvector Neo4j, GraphRAG and Cypher MCP server development LangSmith, LangFuse or similar observability platforms Fine-tuning, embedding model selection or open-weight model deployment Experience working with complex document-heavy ...

secure, observable, reliable and reusable by default. You will also contribute to the production foundations needed to operate AI capabilities reliably, including LLMOps, model access patterns, prompt and agent lifecycle practices, evaluation, observability and secure enterprise integration. This is a hands-on engineering role where the capabilities you build … evaluation practices for agent configurations, prompts and AI workflows, including testing, controlled change and release readinessDesigning secure tool-access patterns for agents, including MCP/tool abstraction, credential management and enterprise API integrationContributing to AgentOps and GenAIOps capabilities, including telemetry, run history, task outcomes, error analysis and feedback loopsContributing ...

high-profile programme building next-generation AI, agentic systems and data platforms. You'll be responsible for developing scalable backend services in Python, building MCP servers and AI-powered workflows, and delivering modern front-end app click apply for full job details ...

technical governance, adoption and stakeholder influence, with an initial focus on landscape assessment, evaluation and standards before moving towards a more embedded, forward-deployed model with delivery teams. Key Responsibilities Lead horizon scanning across the AI tooling landscape and translate emerging capabilities into practical opportunities. Define and promote … practice. Desirable Experience Strong software engineering background within large-scale production environments. Experience with platforms such as AWS Bedrock, Azure OpenAI, AI gateways, MCP gateways or model-routing services. Knowledge of authentication, model access and cost optimisation. Experience evaluating AI tools and techniques using structured testing and measurable ...

partner with the owning engineering team to scope and build it — hands-on throughout, not handing off a ticketGet into the data pipelines, model serving, retrieval and evaluation behind AI-backed features, and the integrations that put them into a real workflowShip a working first version fast, then harden … LLMs in production applications — model APIs, auth, gateways, reliability, latency, cost, observabilityAgentic systems: agentic applications using tools, APIs and orchestration frameworks. Hands-on MCP strongly preferredRetrieval and RAG: production retrieval systems — embeddings, vector stores, indexing, retrieval quality, evaluationAPIs and enterprise integration: REST, auth/authz, data contracts ...

cycle to enable the building and maintenance of our ML systems. Our teams make extensive use of open source technologies such as Kubernetes, KServe, MCP, Envoy AI Gateway, Buildpacks and other cloud-native and GenAI technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact … Senior GenAI Platform Engineer with: Proven years of experience working with an object-oriented programming language (Python, Go, etc.) Experience with GenAI technologies like MCP, A2A, Langgraph, LlamaIndex, Pydantic AI, SDKs and AI-assisted coding toolsA Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience ...

hands-on design and build of AI solutions. Technical depth in how agentic AI systems are built and where they break, including retrieval and context, tool use, orchestration, evaluation and reliability, with … credibility to design and build alongside engineering teams. Able to code in Python and SQL, with working knowledge of LLM APIs, embeddings, agent frameworks, MCP, data pipelines and cloud platforms (Azure, AWS). Deep understanding of clinical operations and wider clinical development, gained in industry, consulting or other relevant settings. ...

Large Language Model (LLM) Technology Lead/Principal ArchitectCareer Level: Manager/Senior Manager/Associate DirectorYOU ARE As a Lead or Principal AI Architect, you will serve as the definitive technical authority on AI architecture within client engagements and across the practice. You will own the complete …/IAP binding, and defense-in-depth enforcement Define the layered guardrail framework applied at every boundary, balancing protection with performance Govern the MCP control plane — registry, gateway, and risk scoring — across all internal and third-party servers Mandate adopt-over-build for productized evaluation and observability stacks Establish FinOps ...

ensuring scalability, resilience, security, and standardized lifecycle management Drive the Zero Ops vision by automating troubleshooting, upgrades, rollouts, capacity management, and operational improvements Operate MCP server infrastructure and implement platform guardrails, runtime policies, model access controls, quotas, and security controls Support reliable platform operations and releases across different environments … correlation, dashboards, and automated health checks Hands-on experience with Dynatrace and Splunk in enterprise environments Understanding of AI platform runtime controls such as model access, quotas, rate limits, cost monitoring, and traceability A collaborative mindset and the ability to support technical rollouts and stable operations across multiple environments ...

risk, and reuse before recommending experiments or enhancements to existing and new ES services. Architect AI-enabled capabilities within ES cloud, identity, API/MCP, integration, connectivity, and observability services; apply secure, reusable enterprise patterns. Lead hands-on evaluations and prototypes; guide solution development and integration through production readiness, with … retrieval when appropriate, tool/agent integration, quality evaluation, model-selection tradeoffs, and non-AI alternatives. Enterprise service integration: Cloud architecture, REST APIs, MCP, identity and authorization, operations tooling, and reusable platform and service patterns. Security and service reliability: Data protection, threat modeling, auditability, observability, resiliency, human oversight ...

quality, and maintainability considerations. Essential Skills & Experience Active SC Clearance (essential). Strong hands-on experience building and deploying agentic AI solutions. Expertise in model selection, prompt engineering, agent orchestration, and tool integration. Experience applying AI across the Software Development Lifecycle … including code generation, testing, documentation, code review, and modernisation activities. Practical exposure to AI engineering tools such as GitHub Copilot, Claude Code, Codex, Kiro, MCP, or similar technologies. Proven track record defining and implementing engineering standards adopted across multiple teams or programmes. Strong stakeholder engagement skills with the ability ...

quality, and maintainability considerations. Essential Skills & Experience Active SC Clearance (essential). Strong hands-on experience building and deploying agentic AI solutions. Expertise in model selection, prompt engineering, agent orchestration, and tool integration. Experience applying AI across the Software Development Lifecycle … including code generation, testing, documentation, code review, and modernisation activities. Practical exposure to AI engineering tools such as GitHub Copilot, Claude Code, Codex, Kiro, MCP, or similar technologies. Proven track record defining and implementing engineering standards adopted across multiple teams or programmes. Strong stakeholder engagement skills with the ability ...

engagements are delivered and how quickly customers realize value. Current platforms include UMP, which migrates customers to Optimizely from any source at scale, and MCP, an AI toolbox that accelerates CMS and Commerce upgrades. The role operates in two modes. You lead a solution through architecture, build, and enablement until … years of experience. Relevant backgrounds include solutions architecture, technical consulting, platform engineering, and product engineering. What success looks likeYou deliver against the roadmap. UMP, MCP, and future initiatives progress from concept to general availability and adoption. You turn challenges into solutions. You convert ambiguous problems into working solutions without waiting ...

acceptance criteria, human oversight and controlled failure behaviour. Implement LLM application patterns including tool and function calling, structured outputs, RAG or graph-based retrieval, context and memory management, multi-agent orchestration, and prompt or configuration versioning. Integrate with ERP and EPM systems, document repositories and workflow tooling, including … Oracle, Workday, Anaplan or OneStream, or to finance processes such as close, planning, order to cash or procure to pay. Experience with MCP, graph or semantic retrieval, data engineering, event-driven integration or workflow orchestration. Experience deploying software or data products on Azure, AWS or GCP, DataBricks, Snowflake, Palantir etc. ...

acceptance criteria, human oversight and controlled failure behaviour. Implement LLM application patterns including tool and function calling, structured outputs, RAG or graph-based retrieval, context and memory management, multi-agent orchestration, and prompt or configuration versioning. Integrate with ERP and EPM systems, document repositories and workflow tooling, including … Oracle, Workday, Anaplan or OneStream, or to finance processes such as close, planning, order to cash or procure to pay. Experience with MCP, graph or semantic retrieval, data engineering, event-driven integration or workflow orchestration. Experience deploying software or data products on Azure, AWS or GCP, DataBricks, Snowflake, Palantir etc. ...

generate and refine Playwright tests rather than relying exclusively on manually written scripts. Understanding of effective prompting and providing appropriate application context to AI tools. Ability to critically assess AI-generated code and identify incorrect assumptions, incomplete coverage or unreliable tests. Enthusiasm for experimenting with new AI capabilities … code generation, tracing and debugging capabilities. Experience using AI agents or browser automation agents to explore applications and generate tests. Experience with Playwright MCP or similar AI-enabled browser interaction tools. Familiarity with API testing and combining API and UI validation. Experience with accessibility testing. Experience testing complex ERP, automotive ...

decisions with long-term maintainability, extensibility, and operational excellence in mind AI Platform Enablement: Evaluate, pilot, and implement emerging AI technologies, large language models, MCP integrations, and agent frameworks that enable intelligent automation across enterprise systems while establishing best practices for responsible adoption Automation & Developer Experience: Build reusable automation frameworks … automation, and software engineering to solve operational challenges Curious, collaborative, and motivated by continuous improvement and thoughtful systems design Bonus: Experience implementing AI agents, MCP integrations, LLM-powered workflows, or enterprise AI platforms Experience with Terraform, Infrastructure as Code, or cloud automation tooling Experience with event-driven architectures, message queues ...

decisions with long-term maintainability, extensibility, and operational excellence in mind AI Platform Enablement: Evaluate, pilot, and implement emerging AI technologies, large language models, MCP integrations, and agent frameworks that enable intelligent automation across enterprise systems while establishing best practices for responsible adoption Automation & Developer Experience: Build reusable automation frameworks … automation, and software engineering to solve operational challenges Curious, collaborative, and motivated by continuous improvement and thoughtful systems design Bonus: Experience implementing AI agents, MCP integrations, LLM-powered workflows, or enterprise AI platforms Experience with Terraform, Infrastructure as Code, or cloud automation tooling Experience with event-driven architectures, message queues ...