YOUR IMPACT
Are you passionate about building mission-critical, high-quality backend systems that are scalable, resilient, and distributed by design, using modern engineering practices in a dynamic environment?
OUR IMPACT
We are Compliance Engineering, a global team of more than 300 engineers and scientists who work on the most complex, mission-critical problems.
We:
- build and operate a suite of platforms and applications that prevent, detect, and mitigate regulatory and reputational risk across the firm.
- have access to the latest technology and to massive amounts of structured and unstructured data.
- design and build scalable backend services, distributed data-processing platforms, APIs, event-driven systems, and operational tooling that power compliance workflows across the firm.
HOW YOU WILL FULFILL YOUR POTENTIAL
As a member of our team, you will:
- partner globally with sponsors, users, and engineering colleagues across multiple divisions to build reliable backend platforms and services,
- learn from experts in distributed systems, data platforms, regulatory technology, and production engineering,
- design, implement, and operate backend services using technologies such as Java, APIs, GraphQL, Elasticsearch, Kafka, Kubernetes, relational databases, and cloud-native deployment patterns,
- build systems that handle large volumes of structured and unstructured data, including real-time processing, messaging, search, workflow orchestration, and integration across services,
- apply strong engineering fundamentals to improve scalability, latency, throughput, reliability, observability, and fault tolerance,
- be able to innovate and incubate new ideas that simplify complex compliance workflows and improve platform resilience,
- be involved in the full software lifecycle: defining, designing, implementing, testing, deploying, monitoring, and maintaining backend systems in production.
AI‑Assisted Engineering & Productivity
In addition, you will:
- Effectively use AI‑assisted software development tools (e.g., GitHub Copilot, Devin, Claude Code, or equivalent) to improve developer productivity and reduce development cycle time.
- Apply AI tools to accelerate:
- code generation and refactoring,
- test creation and coverage improvement,
- debugging, root‑cause analysis, and performance optimization.
- Use AI‑assisted reasoning to understand complex codebases, rapidly prototype solutions, and improve code quality while maintaining strong engineering standards.
- Partner with peers and reviewers to validate, harden, and productionize AI‑generated outputs, ensuring correctness, security, maintainability, and regulatory compliance.
- Identify opportunities where AI tooling can reduce manual effort, minimize rework, and support faster, higher‑quality delivery to production.
QUALIFICATIONS
A successful candidate will possess the following attributes:
- A Bachelor's or Master's degree in Computer Science, Computer Engineering, or a similar field of study.
- 3+ years of professional software development experience, with strong backend engineering experience.
- Strong expertise in Java and backend service development, including API design, concurrency, data structures, and performance-aware programming.
- Experience with automated testing, SDLC concepts, production deployment, monitoring, incident response, and operating reliable software systems.
- Experience designing scalable and distributed systems, including service-to-service communication, asynchronous processing, caching, data persistence, and fault-tolerant architectures.
- Experience building, deploying, or operating backend services on cloud platforms, including cloud-native deployment patterns, managed services, security considerations, and operational best practices.
- The ability (and tenacity) to clearly express ideas and arguments in meetings and on paper.
Experience in some of the following is desired and can set you apart from other candidates:
- Experience building backend platforms, microservices, distributed systems, or data-intensive applications in production environments.
- Strong understanding of system design fundamentals, including scalability, availability, consistency, fault tolerance, latency, throughput, and operational trade-offs.
- Hands-on experience with event-driven architectures, messaging platforms, stream processing, or workflow orchestration using technologies such as Kafka or equivalent platforms.
- Experience with relational databases, data modeling, query optimization, transaction management, and designing reliable data access patterns.
- Experience with search or analytics platforms such as Elasticsearch, OpenSearch, or equivalent technologies.
- Practical knowledge of containerized deployments, Kubernetes, CI/CD pipelines, observability, logging, metrics, tracing, and production support practices.
- Experience with AWS services such as ECS/EKS, Lambda, S3, DynamoDB, RDS, CloudWatch, IAM, or equivalent AWS-native services for building and operating scalable backend systems.
- Demonstrated experience or strong interest in leveraging AI-assisted developer tools to improve engineering productivity while maintaining high standards for correctness, security, reliability, and maintainability.
- Ability to critically evaluate AI-generated outputs and refine them to production-grade quality.
ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit to our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html
© The Goldman Sachs Group, Inc., 2026. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
Skills Required
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or similar
- 3+ years of professional software development experience
- Strong expertise in Java and backend service development (API design, concurrency, data structures, performance-aware programming)
- Experience with automated testing, SDLC concepts, production deployment, monitoring, and incident response
- Experience designing scalable, distributed, fault-tolerant systems (service-to-service communication, asynchronous processing, caching, persistence)
- Experience building, deploying, or operating backend services on cloud platforms and cloud-native deployment patterns
- Ability to clearly express ideas and arguments in meetings and on paper
- Experience with event-driven architectures, messaging/stream processing, or workflow orchestration (e.g., Kafka)
- Experience with Elasticsearch or OpenSearch and search/analytics platforms
- Hands-on experience with containerized deployments and Kubernetes
- Experience with relational databases, data modeling, query optimization, and transaction management
- Experience with AWS services such as ECS/EKS, Lambda, S3, DynamoDB, RDS, CloudWatch, IAM
- Familiarity with CI/CD pipelines, observability (logging, metrics, tracing), and production support practices
- Demonstrated experience or strong interest in leveraging AI-assisted developer tools and validating AI-generated outputs
Goldman Sachs Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Goldman Sachs and has not been reviewed or approved by Goldman Sachs.
-
Healthcare Strength — Coverage includes medical, dental, vision, disability, life and accident insurance, with multiple plan options and most premiums subsidized; coverage often starts on day one. Wellness resources, on-site health centers in some locations, and EAP access reinforce the depth of health support.
-
Parental & Family Support — Family care includes on-site childcare in some offices, expectant parent resources, and transitional programs for returning parents. Feedback suggests parental leave is very generous, with reports of around 20 weeks paid leave and stipends for adoption, surrogacy, and fertility-related services.
-
Retirement Support — The firm provides a 401(k) plan with employer matching contributions and broad financial education to help employees plan for retirement. Resources also support saving for education and preparing for unexpected events.
Goldman Sachs Insights
What We Do
At Goldman Sachs, we believe progress is everyone’s business. That’s why we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, Goldman Sachs is a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices in all major financial centers around the world. More about our company can be found at www.goldmansachs.com






