Senior Engineer II - Agent Harness & Workflow Engineering

IBM

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Work type
On-site
Location
San Jose, CA
Posted
37 days ago

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Similar $185k
$139k most similar roles pay here $232k

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About IBM

IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

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Listed pay typically runs $1,000,000–$1,000,000 across 8 roles with salary data.

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TL;DR · Senior Engineer II - Agent Harness & Workflow Engineering

As a Senior Engineer II on the agent-first engineering team in San Jose, you will build and evolve type-safe AI pipelines for intent analysis, planning, knowledge enrichment, and infrastructure generation across Z, Power, and Cloud platforms using Terraform, Ansible, Pulumi, and native APIs. You’ll design context management, telemetry, and observability for multi-step workflows, own a markdown-based workflow engine supporting parallel execution and cross-domain orchestration, develop a plugin-based tool provider system integrating with secure session management, and advance a robust evaluation framework to ensure AI-generated outputs are production-safe. In the first 90 days, you will onboard onto the Go agent codebase, extend the eval corpus, design a workflow catalog, and implement cross-platform pipeline routing. Strong proficiency in Go is essential, along with experience building execution systems and integrating LLM APIs in production environments.

What you'll do

  • Build type-safe AI pipelines for intent analysis and knowledge enrichment.
  • Extend pipeline routing across Z, Power, and Cloud platforms securely.
  • Design context management and observability for multi-step AI workflows.
  • Develop a markdown-based workflow engine supporting parallel execution.
  • Advance a robust evaluation framework to ensure production safety of outputs.

What we're looking for

  • Strong Go engineering experience with immediate productivity in the language.
  • Experience building execution systems like workflow engines or pipeline frameworks.
  • Practical LLM integration skills including prompt construction and output parsing.
  • Background in quality measurement, evaluation, testing, and regression detection.
  • Understanding of IBM Z, Power, and Cloud infrastructure APIs and operational knowledge.
  • Familiarity with Terraform, Ansible, and infrastructure-as-code patterns.

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