AI Enabled Modernization Agentic Software Engineer Vice President

Goldman Sachs

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Work type
On-site
Location
Seattle, WA
Posted
1 day ago
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Confirmed live today

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Similar $194k
$132k most similar roles pay here $241k

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About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 91 open roles on FindRole.

Listed pay typically runs $130,000–$250,000 across 37 roles with salary data.

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TL;DR · AI Enabled Modernization Agentic Software Engineer Vice President

AI Enabled Modernization - Agentic Software Engineer - Vice President will join the newly formed AI Agentic Systems team to address large-scale application and infrastructure challenges by building and deploying swarms of agents. This role involves designing multi-agent systems for autonomous planning, reasoning, and execution across distributed cloud environments while developing human-in-the-loop systems, evaluation frameworks, and observability mechanisms. The position focuses on automating modernization workflows within a complex technology estate. Candidates must possess proficiency in Python, Go, Java, or Javascript, alongside experience with distributed systems, cloud-native architecture, and LLM-based agents using frameworks like LangGraph or AutoGPT. Key technical domains include data analysis, infrastructure observability, resource optimization, and multi-step task decomposition. The role requires building integrations with APIs, CI/CD pipelines, and data platforms to transform ambiguous business needs into technical agentic workflows.

What you'll do

  • Design and deploy multi-agent systems capable of autonomous planning, reasoning, and execution in distributed cloud environments.
  • Build human-in-the-loop systems and evaluation frameworks to enable continuous improvement of AI agents.
  • Develop observability mechanisms to monitor and improve agentic performance.
  • Integrate agentic systems with APIs, developer tools, CI/CD pipelines, and data platforms.
  • Translate ambiguous business needs into technical workflows for various firm-wide units.
  • Build systems to automate and validate application modernization workflows across complex technology estates.
  • Develop automated solutions for data analysis, infrastructure observability, resource optimization, and task decomposition.

What we're looking for

  • Proficiency in Python, Go, Java, Javascript, or similar languages.
  • Deep understanding of distributed systems and cloud-native architecture (AWS, Azure, or private clouds).
  • Direct experience deploying and operating LLM-based agents in production environments.
  • Familiarity with frameworks such as LangGraph, AutoGPT, or custom-built orchestration layers.
  • Experience designing benchmarks, evaluations, and quality metrics for AI systems.
  • Proven track record of applying agentic patterns to at least two areas: data analysis, observability, optimization, or planning.
  • Demonstrated interest in emerging technologies like Multi-Agent Reinforcement Learning (MARL) and swarm intelligence (preferred).
  • Familiarity with Model Context Protocol (MCP), A2A, and other standards for agent-to-tool communication (preferred).

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