Technology Risk - Vice President, Agentic Systems Engineer / Technical Lead, Dal

The Goldman Sachs Group Inc
Dallas, TX, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon S3 Software Applications Automated Storage and Retrieval Systems User Authentication Cloud Computing Security Cyber Security Continuous Integration Distributed Systems Amazon DynamoDB
+16 more
Identity and Access Management Python (Programming Language) Software Engineering Software Systems Software Vulnerability Management Workflow Management Systems Enterprise Software Applications Spring Cloud Large Language Models Multi-Agent Systems Software Security State Machines AI Platforms Kubernetes Information Technology Cloudwatch

Job description

As a Vice President within our Engineering organization, you will lead the design and development of production-grade agentic AI systems that automate complex business and cybersecurity workflows across the firm. You will help establish the architecture, controls, and engineering standards required to safely scale AI-powered automation in a highly regulated environment., * Design and develop scalable agentic AI systems capable of reasoning, planning, retrieving information, invoking enterprise tools, and executing complex multi-step workflows.

  • Build reusable platform capabilities for orchestration, memory, tool integration, observability, governance, evaluation, and human-in-the-loop controls.
  • Define architecture patterns that balance AI-driven reasoning with deterministic software systems, ensuring reliability, transparency, and auditability.
  • Partner with cybersecurity, engineering, and business teams to identify automation opportunities and deliver production-ready solutions.
  • Develop secure integrations with internal platforms, enterprise data sources, development tooling, and operational workflows.
  • Establish testing and evaluation frameworks to measure quality, reliability, performance, and business outcomes.
  • Drive engineering best practices across software development, deployment, monitoring, and operational support.
  • Mentor engineers and provide technical leadership across multiple initiatives., Successful candidates will deliver secure, scalable, and measurable AI-driven automation solutions while establishing reusable platform capabilities that accelerate adoption across the firm. They will influence engineering standards, mentor teams, and help shape the long-term strategy for enterprise AI and agentic systems. The Goldman Sachs Group, Inc., 2018. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.

Requirements

This role requires a strong software engineering foundation, deep understanding of AI systems, and the ability to partner closely with engineering, cybersecurity, and business stakeholders to transform emerging technologies into enterprise solutions that deliver measurable impact., * Bachelor’s degree in Computer Science, Engineering, or a related technical discipline.

  • Extensive experience building and operating large-scale distributed systems, cloud-native applications, or enterprise software platforms.
  • Hands-on experience developing AI-powered applications utilizing large language models, tool integration, retrieval systems, and workflow orchestration frameworks.
  • Strong proficiency in Python and modern software engineering practices, including APIs, testing, CI/CD, production monitoring, and observability.
  • Experience building solutions on AWS, including services such as Bedrock, Lambda, ECS/EKS, Step Functions, S3, DynamoDB, IAM, and CloudWatch.
  • Strong understanding of security architecture, authentication, authorization, data protection, and governance controls.
  • Proven ability to translate complex business requirements into scalable technical solutions.
  • Excellent communication and stakeholder management skills., * Experience building AI platforms or agentic systems in cybersecurity, financial services, or other regulated industries.
  • Familiarity with frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Strands Agents, or similar orchestration technologies.
  • Experience supporting security operations, cloud security, vulnerability management, identity and access management, or application security functions.
  • Experience evaluating and implementing enterprise AI platforms, including build-versus-buy decision frameworks.
  • Demonstrated track record of leading engineering teams and driving technical strategy.

About the company

Engineering is at the heart of Goldman Sachs. We build scalable platforms and technologies that power the firm’s global business while maintaining the highest standards of security, reliability, and operational excellence.

Our team is focused on developing next-generation agentic systems and AI-driven platforms that enable intelligent automation, improve operational efficiency, and enhance decision-making across complex enterprise environments.

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