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Software Engineer - Global Investment Research - Vice President

Job in West Midlands, Birmingham, West Midlands, B1, England, UK
Listing for: Goldman Sachs
Full Time position Listed on 2026-11-12
Job specializations:
Salary/Wage Range or Industry Benchmark: 90000 - 140000 GBP Yearly GBP 90000.00 140000.00 YEAR

Job Description & How to Apply Below

Location: West Midlands

What We Do

At Goldman Sachs, our Engineers don't just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action.

Drive new businesses, redefine finance using AI, and seize opportunities at market speed.

Job Description

At Goldman Sachs, our Engineers don't just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action.

Drive new businesses, redefine finance using AI, and seize opportunities at market speed.

In an era defined by AI, Engineering isn't just central – it's the driving force behind our business. Our dynamic environment demands innovative strategic thinking and immediate, impactful solutions. Ready to push the limits of digital possibility? Begin your journey here.

Who We Look For

Goldman Sachs Global Investment Research (GIR) is seeking an Agentic Systems Engineer to build, enhance, and product ionize intelligent research tools and automated agentic pipelines. You will collaborate with senior engineers to develop end-to-end full-stack applications, implement advanced RAG components, and integrate AI services into mission-critical GIR platforms.

How You Will Fulfill Your Potential
  • Feature Engineering:
    Build and maintain end-to-end full-stack features, integrating analyst-facing frontends with backend APIs and microservices implemented in Java or Python.
  • Gen AI & Agent Implementation:
    Implement and optimize advanced RAG pipelines and stateful multi-agent workflows using Google ADK, Lang Chain, Lang Graph, AWS Bedrock, or equivalent technologies, incorporating structured outputs, tool calling, and human-in-the-loop steps.
  • Evaluation & Benchmarking:
    Implement automated offline and online evaluation suites using tools such as Braintrust, Agent Core Eval, equivalent industry solutions, or custom test harnesses to assess contextual relevance, groundedness, and hallucination reduction.
  • Cloud & Data Integration:
    Deploy and connect AI components with enterprise services on AWS, configuring Lambda, ECS/Fargate, Event Bridge, S3, IAM policies, and API Gateway endpoints.
  • Observability & Incident Support:
    Monitor model and service performance using Cloud Watch and distributed tracing; triage production incidents, conduct root-cause analyses, and optimize token/resource consumption.
  • SDLC Discipline:
    Actively participate in peer code reviews, write automated unit and integration tests, maintain CI/CD pipelines, and document integration patterns and data models.
  • Agile

    Collaboration:

    Coordinate with business stakeholders and cross-functional teams in Agile sprints to translate research requirements into deliverable technical stories.
Basic Qualifications
  • 7+ years of hands-on software engineering experience with proficiency in Java or Python, combined with modern full-stack web technologies (e.g., React, Type Script, FastAPI, Spring Boot).
  • Bachelor’s degree in Computer Science, Software Engineering, Applied Mathematics, or a related quantitative field.
  • Working knowledge of core AWS services, including Lambda, ECS/Fargate, S3, Event Bridge, Cloud…
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