, or workflow automation, together with familiarity with MCP, tool calling, agent orchestration, evaluation, or observability

, pharmaceuticals or life sciences, including deploying agentic AI. CI/CD best practices, including API development, MCP implementation

AI using Google ADK. Design, develop and test AI Agents and work with Model Context Protocol (MCP) and MCP servers. Write... with Model Context Protocol (MCP) and AI/data/service integration is highly desirable. Strong understanding of REST APIs

tooling — Cursor, Codex CLI, Cline, Aider): writing custom skills, building subagent systems, implementing MCP servers... (or equivalent agentic CLI tooling) skills, subagents, and MCP servers that become the standard AI tooling distributed to all client

coding workflows, such as running AI agents on multi-step tasks, writing custom rules or context files, or using MCP servers

of discovery - across AI and traditional search. Yext's API-first architecture connects structured data to APIs, MCP servers

prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI

is strongly preferred. MCP – Microsoft Certified Professional is strongly preferred. Linux/Solaris/UNIX System Administration

, and Skills: Experience with agent frameworks and protocols (Google ADK, LangGraph, MCP, A2A, AG-UI) Experience with Databricks

audiences Preferred qualifications, capabilities, and skills Experience with agent frameworks and protocols (MCP, A2A

protocols and frameworks such as MCP, A2A, AG-UI, Google ADK, or LangGraph Experience with agent payment and mandate patterns

MCP (Model Context Protocol) servers that provide agents secure access to CRM, supplier directory, and payments data..., and Skills: Experience with agent frameworks (e.g., Google ADK, LangGraph) and agent protocols such as MCP, A2A, or AG-UI

(Python, JavaScript/Node, APIs, SDKs), and fluent with AI development tooling (Claude, Cursor, agent frameworks, MCP). A CS... systems the field deploys into: demo automation, agent and MCP skill packages, workflow plugins, and the discoverable asset

Center APIs, MCP, and integrations Find the root cause. Read device, agent and browser logs, reproduce issues in a test

development: Usage of LLM models for application, Agentic implementation, usage of tools to integrate data into LLM context, MCP

for security/compliance risk before merge. Familiarity with prompt-based tooling and MCP (Model Context Protocol) integrations

using A2A and integrate tools and data through MCP servers (Bitbucket, Confluence, Databricks, Kubernetes, Snowflake, Splunk... Preferred Qualifications, Capabilities, and Skills: Experience with agent frameworks or runtimes, A2A, or MCP Agent memory

, including MCP/tool abstraction, credential management and enterprise API integration Contributing to AgentOps and GenAIOps

, including MCP/tool abstraction, credential management and enterprise API integration Contributing to AgentOps and GenAIOps

for stakeholders at all levels. Familiarity with AI technologies (such as LLMs and MCP), data ingestion methods and marketing