10 of 10 Model Context Protocol Jobs in the North East

role is engineering AI agents and agentic workflows. You will design how agents use trusted knowledge, approved tools, Model Context Protocol (MCP) services, approvals, human hand-offs and safe failure paths. You will ensure that evaluation, observability, identity, permissions and data boundaries are built into delivery rather … agents and agentic workflows using trusted knowledge, tools, actions, approvals, human hand-offs, evaluation and safe failure paths. • Design and implement integrations with approved MCP servers and lead development of MCP tools or services using secure, reusable patterns. • Integrate Power Platform and AI solutions with Microsoft 365, SharePoint, Microsoft Graph ...

admin position. A. Agentforce Architecture & System Design Solution Architecture: Translate complex enterprise business processes into end-to-end agentic workflows (Intent $rightarrow$ Agent $rightarrow$ Context $rightarrow$ Reasoning $rightarrow$ Actions $rightarrow$ Systems $rightarrow$ Outcome). Core Agent Engineering: Design, configure, and build enterprise agents using Agent Builder, Agentforce Studio, Agent … search, and Knowledge libraries. System Interoperability: Architect REST API callouts, event-driven integrations, and MuleSoft platform pipelines, incorporating Model Context Protocol (MCP) standards. D. Testing, Security & Strategic Advisory Testing & Quality Assurance: Drive automated testing and multi-turn conversation tracing using the Agentforce Testing Center. Security & Guardrails: Design ...

admin position. A. Agentforce Architecture & System Design Solution Architecture: Translate complex enterprise business processes into end-to-end agentic workflows (Intent $rightarrow$ Agent $rightarrow$ Context $rightarrow$ Reasoning $rightarrow$ Actions $rightarrow$ Systems $rightarrow$ Outcome). Core Agent Engineering: Design, configure, and build enterprise agents using Agent Builder, Agentforce Studio, Agent … search, and Knowledge libraries. System Interoperability: Architect REST API callouts, event-driven integrations, and MuleSoft platform pipelines, incorporating Model Context Protocol (MCP) standards. D. Testing, Security & Strategic Advisory Testing & Quality Assurance: Drive automated testing and multi-turn conversation tracing using the Agentforce Testing Center. Security & Guardrails: Design ...

this position you will play a key part in:* Designing and delivering end-to-end AI/ML systems, from data preparation and model development to model deployment, feature stores, model management and monitoring model management* Delivering solutions using the latest GenAI and Agentic Frameworks, such … Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar.* Ability to design and implement RAG pipelines, agentic workflows, MCP and integration with LLM APIs (OpenAI, Anthropic, Hugging Face OR similar).* Proficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes. ...

grade LLM-powered features and applications Building AI agents, conversational experiences and intelligent workflows Working with technologies such as AWS Bedrock, agent frameworks and MCP Integrating LLM capabilities into existing applications, APIs and datasets Designing hybrid solutions combining AI, rules-based logic and proprietary data Prototyping ideas quickly, testing them … Generative AI Building production applications using commercial or open-source LLMs AI agents and agentic architectures AWS Bedrock or comparable cloud AI platforms MCP/tool-enabled LLM applications Building chatbots or conversational applications API and application integration Prompt and context engineering Retrieval and grounding techniques Model evaluation ...

team and set the bar in design reviews and code reviews. Engage with the open source and agentic development community around sandboxing, MCP, and related ecosystems. Participate in on-call rotations and respond to critical stability issues affecting users. Document your work clearly and share knowledge with the rest ...

expand into agentic solution delivery and broader business transformation. Our conviction is that engineers are uniquely positioned to lead this transformation. The strongest mental model for designing, deploying, and governing AI agents in production lives in software engineering. The teams that change how their organization builds software … assumptions, risks, milestones, and dependencies Embed with customer teams to co-build agentic applications on the Claude developer platform Build technical artifacts — evaluation frameworks, MCP servers, sub-agents, and deployment configurations — tailored to the customer's stack What Success Looks Like Customers move from proof-of-value to production Engineering ...

build pipelines Software supply chain integrity Container security and governance AI/ML workload governance (where applicable) AI agent architecture patterns: isolated execution environments, MCP policy enforcement, model artifact provenance Partner with Sales Engineers and Post-Sales teams to ensure technical continuity without owning deal cycles. What … packaging, dependency management, reproducibility, and governance considerations within containerized environments. Practical Experience with AI coding agent runtimes and sandboxed execution environments (e.g., agent isolation, MCP tool governance) Familiarity with Docker SBX and MCP Gateway as enterprise controls for agentic AI workloads Familiarity with secure software supply chain practices, including SBOM ...

moving from a traditional SaaS posture to a platform built around agents - parent agents fronting our compensation data, specialist agents underneath, durable workflows, an MCP-based tool layer, and an eval harness to maintain consistency. You’ll own architecture and technical design across the stack: the customer-facing … have Production experience with agentic systems - tool calling, multi-step orchestration, LLM evals. Workflow engines (Temporal, Cadence, Step Functions) - even if not Temporal specifically MCP, Anthropic SDK, or other LLM platform work Building developer platforms, internal SDKs, or framework-shaped surfaces Eval-driven development, prompt engineering at scale, LLM-judge ...

agent can use?" before asking "does this data exist?". As that foundation takes shape, your scope expands naturally into Grip's MCP design, agentic workflows and AI system architecture. In your own workflow, agentic tooling is already the default. You use Claude Code, GitHub automations and agents to manage … Define success metrics and build feedback loops that keep product decisions grounded in data. Expanding into AI & agentic - as your scope grows Contribute to MCP tool design, shaping how Grip's data is exposed and consumed within agentic systems. Work with the Data and AI squad to identify where agentic ...