IBM watsonx AI Engineer / Orchestrate Agent Engineer
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- Build production-minded AI solutions with watsonx, strong retrieval and explicit agent architecture
- Develop and connect governed agents with watsonx Orchestrate ADK, MCP and multi-agent standards
- Evaluate, govern and operate agent portfolios with observability, security and human oversight
Benchmark: IBM AI & watsonx careers + current Client Engineering / watsonx Orchestrate agent-platform signals (current Sep 2026). Market refresh: watsonx.ai; watsonx Orchestrate ADK; LangGraph import; Python/OpenAPI tools; MCP and A2A; agent memory; Agent Catalog; AgentOps, Trace Inspector and evaluation; watsonx.governance / Agentic Control Plane; OpenTelemetry observability, security and measurable enterprise value.
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Build production-minded AI solutions with watsonx, strong retrieval and explicit agent architecture
AI engineering foundations + watsonx solution patterns
Coverage: Python / APIs / watsonx.ai / Granite & Frontier Models / RAG / Embeddings / Deployment / Business Value
RAG, vector grounding + persistent agent memory
Coverage: watsonx.ai / Retrieval / Vector Databases / Grounding / Agent Memory / Context / Knowledge / Cost-Aware Design
Develop and connect governed agents with watsonx Orchestrate ADK, MCP and multi-agent standards
watsonx Orchestrate ADK + tool-driven agent development
Coverage: Orchestrate ADK / Python Tools / OpenAPI / MCP Toolkits / LangGraph Import / Local Testing / Deployment / Observability
Orchestration, MCP + multi-agent collaboration
Coverage: MCP / A2A / Collaborator Agents / Agent Catalog / Orchestration / ReAct / Distributed Workflows / Tool Routing
Evaluate, govern and operate agent portfolios with observability, security and human oversight
AgentOps, evaluation + observability-driven optimization
Coverage: AgentOps / Trace Inspection / LLM-as-a-Judge / Test Cases / User Simulation / OpenTelemetry / Quality-Cost-Latency
Governance, security + human-in-the-loop production controls
Coverage: watsonx.governance / Agentic Control Plane / IAM / Policies / Prompt Injection / HITL / Audit / Safety / Compliance
Role-Readiness Proof / Capstone
Build a governed enterprise agent solution using IBM watsonx. Start with a Python/API service or watsonx.ai component grounded in an enterprise knowledge source; implement an agent in watsonx Orchestrate with ADK, explicit instructions and typed tools; add an OpenAPI or Python tool plus a remote MCP toolkit; use collaborator agents or A2A when decomposition improves outcomes; add memory only where it changes task success; create representative test cases and user simulations, inspect traces and use AgentOps-style evaluation to improve prompts, routing and tools; enforce identity, connection secrets, policy, data isolation and human approvals; register/govern the agent portfolio through the control plane or watsonx.governance; deploy with OpenTelemetry-style observability, latency/cost targets and incident procedures; then prove measurable client or business value with a production-readiness package.
Proof Rubric
- Prove end-to-end engineering judgment: appropriate model and retrieval choices
- trustworthy grounding
- high-quality tool and MCP contracts
- correct orchestration and A2A boundaries
- disciplined memory use
- reproducible test suites and simulated-user evaluation
- actionable traces and failure analysis
- measurable quality, latency and cost improvement
- strong identity, policy, data and human-approval controls
- governance visibility across agents and tools
- reliable deployment and recovery
- and traceable business outcomes showing why the solution should scale beyond a pilot