The Core Engineering - Search & Entity Model Eng - Associate - Bengaluru

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 engineers and scientists working on complex, mission-critical problems at the intersection of regulatory technology, scalable platforms, data, and AI.

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.

The firm is investing to uplift and rebuild the Compliance application portfolio, with a focus on scalable backend platforms, data-intensive systems, and AI-enabled capabilities.

To achieve this, Compliance Engineering is looking for backend software engineers who can help build the platforms, services, and data capabilities 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 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