151 to 175 of 197 Model Context Protocol Jobs

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 ...

want to talk to you! Understand Agent Interoperability - Map and integrate external agents from hyperscalers (e.g. Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate. Enable Conversational & Background Agents - Use Agentforce Studio and Agent Builder to configure chat and background agents; integrate with external channels … Agentforce and deep fluency with D360 and core Salesforce platform services. Advanced Integration - Experience integrating Salesforce with external agents via APIs and open standards (MCP, A2A).Governance & Observability - Familiarity with prompt governance, observability, and monitoring frameworks. Cross-Platform Background - Background in cross-platform integrations (e.g., Hyperscaler SDKs to Salesforce Flows ...

Experience with "platform as a product" or developer experience work: interviewing users, caring about onboarding, measuring adoption. Experience maintaining AI skill files, agent instructions, MCP servers, or similar structured context for coding agents. Experience with Kubernetes-related developer tooling (Make, Kustomize, Helm) and with simplifying local workflows. Experience integrating ...

regulatory requirements Establish enterprise standards and reference architectures for data products, semantic layer services, AI/LLM gateways, agent orchestration, and API- and MCP-based data access Architect the platform layers that let AI systems and agents find, trust, ask, and act on enterprise data - including data product interfaces, semantic … from registered assets to autonomous-grade, AI-ready products Establish foundational patterns for retrieval, context enrichment, grounding, and tool exposure (RAG, semantic layer, MCP tool surfaces) to support agentic and real-time decisioning use cases Engineering & Infrastructure Lead engineering of scalable, secure platform infrastructure on AWS (S3, Lake Formation ...

tool, built while the value case is made Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) Iterating in short loops: demoing every few days, taking feedback, changing course without ceremony Engineering for production from day one: guardrails, security … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

experience with C# ideally Python experience Entra experience Azure Cloud experience - including Azure functions such as Service Bus, Azure DevOps AI Foundry API MCP Frontier AI tools and Models Large Language Models SQL DevOps understanding/experience Retrieval Augmented Generation (RAG) Desirable experience: Experience with other cloud platforms Azure certifications … Solutions Architect, AI Foundry, Azure, AZ-305, AZ-104, AI-103, TOGAF, Zachman, Python, C#, Agile, Azure AI, Agentic, OpenAI, LLM, Integration, API, MCP, Retrieval Augmented Generation, RAG, SQL, PostgreSQL, DevOps, Azure Functions, Service Bus, Cosmos, Solutions Architect, AI Architect, AI Solutions Architect, AI Foundry, Azure ...

Databricks, exposed as self-service products to use case and tenant teams Drive AI services enablement across the platform, delivering shared capabilities (model access, RAG and retrieval … services, evaluation, guardrails, and orchestration) that let teams build and deploy AI solutions faster Champion the creation of reusable assets and accelerators - agent templates, MCP tools and servers, prompt and evaluation libraries, and reference patterns - that accelerate the development and adoption of AI agents across the enterprise Lead hybrid technical ...

tool, built while the value case is made Delivering client POCs and MVPs: RAG pipelines, agent architectures, LLM integrations and protocol-driven tooling (MCP, tool orchestration) Iterating in short loops: demoing every few days, taking feedback, changing course without ceremony Engineering for production from day one: guardrails, security … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

Proficiency: Leverage agentic development environments such as Kiro (and similar AI-assisted IDEs) to accelerate development workflows, including spec-driven development, agent hooks, MCP server configuration, and AI-assisted code generation. Pre-Production Validation: Guide customers through testing, evaluation, and validation of AI agent performance against defined success criteria before … strategies and evaluating model performance across different foundation models * Building Lambda functions and API integrations that serve as tools for AI agents * Configuring MCP servers to expose customer APIs, databases, and tools in a standardized format for agent consumption * Designing A2A workflows where Amazon Connect agents hand ...

PyTorch; model servers such as AWS Bedrock; MLOps such as ML Flow or Sagemaker; agent/AI orchestration such as LangGraph or MCP libraries Strong programming skills, especially in Python (other languages like C++, Scala, Rust etc are bonuses). Practical experience implementing and deploying using various techniques including ...

Databricks, exposed as self-service products to use case and tenant teams Drive AI services enablement across the platform, delivering shared capabilities (model access, RAG and retrieval … services, evaluation, guardrails, and orchestration) that let teams build and deploy AI solutions faster Champion the creation of reusable assets and accelerators - agent templates, MCP tools and servers, prompt and evaluation libraries, and reference patterns - that accelerate the development and adoption of AI agents across the enterprise Lead hybrid technical ...

Doing Contributing to the development of our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Helping design internal AI tooling to accelerate delivery Supporting our upskilling programme with technical AI knowledge-sharing Keeping across emerging AI tools, frameworks and protocols … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

technical and forward-thinking Principal Architect to lead AI-enabled architecture strategy focused on areas such as: Agentic Security and Agentic Platform Enablement, including MCP ecosystem AI-led Global Servicing and Conversational Technology Low-Latency and Critical Payment platforms API and Architectural Best Practices In addition to technical areas … enterprise standards, AI and automation, and horizontal influence. ResponsibilitiesDefine and advance the AI and agentic platform architecture strategy, including a focus on Agentic security, MCP ecosystem enablement, and flexibility of expansion to SaaS providers, while also allowing for maturing home-grown AI capabilities. Support architecture needs across Global Servicing & Corporate ...

research, secure code review, developer enablement, and security automation. Explore, evaluate, and build automation using modern LLM tooling and integration patterns, including custom skills, MCP servers, agentic workflows, retrieval-augmented workflows, and integrations with development and security tooling. You'll need to have: A strong core engineering background with … security assessments, vulnerability research, secure code review, developer enablement, or security automation. Familiarity with LLM automation concepts and tooling, such as custom skills, MCP servers, agentic workflows, retrieval-augmented workflows, or integrations with development and security tooling. Knowledge of open source software component management, Software Composition Analysis, and related security ...

enterprise systems across API, streaming, batch, and self-service access channels. Create consistent interfaces that support human users, analytics tools, applications, AI agents, MCP-compatible clients, and LLM-powered experiences. Partner with Product, Technology, and Customer teams to ensure new initiatives align with platform architecture and long-term strategic goals. … communication skills, with the ability to influence both technical and executive audiences. Nice-to-haveLakehouse architectures. Semantic technologies or knowledge graphs. Event streaming platforms. MCP or AI integration frameworks. Enterprise integration patterns. Financial services or RegTech experience. Identity and access management. API management platforms. To learn more about our values ...

oversee AI/MLOps lifecycle capabilities, including monitoring, tracing, evaluation, operational readiness and controlled transition into production Define and guide API-first and MCP-based integration patterns, including secure access to data and services through the project's API/MCP gateway Jointly with Risk Management/Compliance, evolve … architecture patterns, AI/MLOps lifecycle requirements, monitoring and evaluation, and the transition of AI solutions into controlled operations You have experience with MCP/API-first development practices and designing secure integrations between AI services, data products and enterprise applications You understand AI governance, risk, guardrails, access control ...

permissions, and in ways enterprises can trust. We ship standards and services used by claude.ai, Claude Code, Cowork, and the API. We own the MCP proxy that routes every tool call and the OAuth and token management that keeps connections authenticated. We're also core contributors to the MCP spec … infrastructure that is reliable by default. What you'll doYou'll design, build, and operate the core connectivity infrastructure behind external tool calls — the MCP proxy and the OAuth and token management systems that keep connections authenticated. You'll own reliability for infrastructure that other teams and external partners depend ...

PyTorch; model servers such as AWS Bedrock; MLOps such as ML Flow or Sagemaker; agent/AI orchestration such as LangGraph or MCP libraries \n Strong programming skills, especially in Python (other languages like C++, Scala, Rust etc are bonuses). Practical experience implementing and deploying using various techniques ...

Doing Contributing to the development of our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Helping design internal AI tooling to accelerate delivery Supporting our upskilling programme with technical AI knowledge-sharing Keeping across emerging AI tools, frameworks and protocols … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

Doing Contributing to the development of our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Helping design internal AI tooling to accelerate delivery Supporting our upskilling programme with technical AI knowledge-sharing Keeping across emerging AI tools, frameworks and protocols … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

Doing Contributing to the development of our internal AI platform Building AI-powered client solutions: RAG pipelines, agent architectures, LLM integrations, protocol-driven tooling Helping design internal AI tooling to accelerate delivery Supporting our upskilling programme with technical AI knowledge-sharing Keeping across emerging AI tools, frameworks and protocols … projects, not just professional work (API integrations, prompt engineering, agent workflows, RAG systems) Proficiency in 2+ modern programming languages Awareness of evolving AI tooling (MCP, A2A, or similar) Some consultancy or client-facing experience, or a strong interest in moving into it Desirable: Vector databases, embeddings, fine-tuning Cloud experience ...

event-driven integration (e.g. API gateways, service contracts, event streaming) and enterprise GenAI (e.g. foundation model gateways, agent-to-tool protocols such as MCP and A2A, agent identity and guardrails). You must have deep, hands-on experience with at least one API/integration gateway platform (e.g. Kong … possibilities of a contract-first integration layer and a governed GenAI platform, i.e. API and event-driven architecture, agent-to-tool protocols such as MCP and A2A, and a single enterprise front door for foundation models. Finding great answers to complex and ambiguous questions, and connecting and collaborating across teams ...

focus of the role Design and build production systems in Go, with work across React and TypeScript where needed. Evolve agent execution, tool use, context management, streaming, and long-running workflows. What we're looking … Strong hands-on experience with Go, React and TypeScript. Hands-on experience building systems around LLMs and agentic workflows- any AI, LLM, OpenAI, Claude, MCP This is a start up technology business so any experience in a start up is beneficial but not essential This role is live ...

clinical trials. Trials in these diseases have small patient populations, investigator-led or nonprofit funding and little operational support, and they often stall on protocol quality, operational risk and site start-up. Claude can help teams design better trials and start them sooner. The second is drug repurposing: finding … literature, omics and patient data, and assemble the evidence so the partner can decide the next step. Build reusable infrastructure other institutions can adopt (MCP servers for biomedical data sources, agent skills, benchmarks grounded in real clinical questions), and feed what you learn in the field back to product, engineering ...

D360Build proof-of-value demos (target: under two weeks) with AEs/SEs to accelerate buying decisionsFluent in headless architecture and AI-driven agents (MCP, A2A) — always applied through a data-first lensLong-term trusted advisor to strategic accounts, beyond any single deal3. Reference Architecture & Technical GTMBuild reference architectures … Skill SetData Platforms: Cloud DWH/DL (GCP, Snowflake, Databricks, AWS, Azure), ingestion pipelines, data modelling, governanceAI & Agentic: GenAI, RAG, vector stores, agent lifecycle, MCP/A2A interoperabilitySalesforce Platform: Data 360, Agentforce, Agent Builder — deep architectural fluencyIntegration/BI: MuleSoft, hyperscaler SDKs, Tableau/PowerBI/Looker familiarityKey QualitiesFuturist — connects ...