Corporate Planning & Management - CPM Platform Engineering - Associate - Bengaluru

Goldman Sachs · Bengaluru · 3+ yrs experience · Posted 2026-03-13

Tech stack: Elasticsearch, Java, JavaScript, Kafka, Linux, MongoDB, Python, React, TypeScript, Unix

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About the role

Corporate Planning & Management (CPM)
unifies Finance & Planning, Global Procurement, Product & Reporting and CPM Engineering teams to deliver business planning and analytics, expense management, third party risk management, sustainability strategy for our operations and supply chain, and governance strategies across the firm.
CPM Engineering
provides engineering solutions that enable the firm to manage third-party spend & risk management, plan budgets, forecast financial scenarios, allocate expenses and support corporate decision making in-line with the firm’s strategic objectives.
Why does this role stand out:
Direct business impact - your work shapes how the firm plans, spends, forecasts, and makes strategic decisions.
Build solutions across data, automation, platforms, and decision-support tools, not just isolated applications.
Cross-functional exposure - partner closely with finance, procurement, product, and risk leaders across a global organization.
Complex, meaningful problems - work on systems that improve transparency, controls, efficiency, and scalability across enterprise operations.
We offer:
The opportunity to work on
high-impact platforms
that directly influence firm-wide financial planning and operational resilience
Access to
modern cloud-native architectures
, distributed systems, and large-scale data pipelines
A forward-looking environment where
AI tools, agentic frameworks, and intelligent automation
are actively shaping the next generation of our solutions
A collaborative, global team where you can learn from experts and grow your career
Responsibilities:
- Software Developer
- on our team, you will:
- Design, develop, and maintain
- full-stack applications across the entire software lifecycle from requirements gathering and architecture through implementation, testing and deployment
- Build responsive, intuitive experiences
- robust back-end services
- that power financial planning, expense management, and risk platforms
- Leverage AI tools and techniques
- (e.g., code-generation assistants, LLM-powered automation, prompt engineering, Spec-Driven Development) to accelerate development, improve code quality, and enhance platform capabilities
- Contribute to the design and development of AI-driven and agentic solutions
- , including intelligent workflows, retrieval-augmented generation (RAG) pipelines, and automated decision-support systems
- Collaborate globally
- with sponsors, users, and engineering colleagues across multiple divisions to create end-to-end solutions that meet complex business requirements
- Participate in code reviews
- to ensure quality, maintainability, and adherence to engineering best practices
- Take technical ownership
- of features and components, managing multiple stakeholders and driving delivery within a global team
- Stay current
- with the latest advancements in AI/ML platforms, tools, and software engineering practices to continuously improve our solutions
Qualifications:
- Required
- Bachelor's or master's degree in computer science, Computer Engineering, or a similar field of study.
- 3+ years of proficiency in Java
- (preferred) or another major programming language (Python), with readiness to upskill where necessary
- Full-stack development experience
- comfortable building both front-end (e.g., React, JavaScript/TypeScript) and back-end (e.g., Java, Spring Framework, APIs) components
- Strong analytical and problem-solving skills
- experience with algorithms, data structures, and software design
- Excellent programming skills - developing, debugging, testing, and optimizing code
- Proficiency in utilizing AI tools
- for software development (e.g., AI-assisted coding, code review tools, LLM-based productivity tools)
- Foundational understanding of AI and agentic systems
- familiarity with concepts such as large language models, prompt engineering, retrieval-augmented generation (RAG) etc.
- Knowledge of
- cloud-native solutions
- Comfortable with technical ownership, managing multiple stakeholders, and working as part of a global team
- Preferred - Experience That Can Set You Apart
- Experience with
- distributed databases
- such as MongoDB and/or Elasticsearch
- open-source messaging systems
- like Kafka
- Systems experience in
- UNIX/Linux
- , especially in scaling for performance and debugging complex distributed systems
- API design
- creating interconnected services, message buses, or real-time processing systems
- Exposure to
- GenAI techniques
- including RAG pipelines, model fine-tuning, agentic frameworks (e.g., LangChain, AutoGen), or embedding models and vector databases
- Familiarity with
- MLOps practices
- including CI/CD for ML, model deployment, and monitoring
- Knowledge of the
- financial industry
- corporate planning, expense management, or risk functions

Qualifications

- Bachelor's or master's degree in computer science, Computer Engineering, or a similar field of study.
- 3+ years of proficiency in Java
- (preferred) or another major programming language (Python), with readiness to upskill where necessary
- Full-stack development experience comfortable building both front-end (e.g., React, JavaScript/TypeScript) and back-end (e.g., Java, Spring Framework, APIs) components
- Strong analytical and problem-solving skills experience with algorithms, data structures, and software design
- Excellent programming skills - developing, debugging, testing, and optimizing code
- Proficiency in utilizing AI tools for software development (e.g., AI-assisted coding, code review tools, LLM-based productivity tools)
- Foundational understanding of AI and agentic systems familiarity with concepts such as large language models, prompt engineering, retrieval-augmented generation (RAG) etc.
- Knowledge of cloud-native solutions
- Comfortable with technical ownership, managing multiple stakeholders, and working as part of a global team
- Experience That Can Set You Apart
- Experience with distributed databases such as MongoDB and/or Elasticsearch open-source messaging systems like Kafka
- Systems experience in UNIX/Linux especially in scaling for performance and debugging complex distributed systems API design creating interconnected services, message buses, or real-time processing systems
- Exposure to GenAI techniques including RAG pipelines, model fine-tuning, agentic frameworks (e.g., LangChain, AutoGen), or embedding models and vector databases
- Familiarity with MLOps practices including CI/CD for ML, model deployment, and monitoring
- Knowledge of the financial industry corporate planning, expense management, or risk functions

Responsibilities

- Software Developer on our team, you will:
- Design, develop, and maintain full-stack applications across the entire software lifecycle from requirements gathering and architecture through implementation, testing and deployment
- Build responsive, intuitive experiences robust back-end services that power financial planning, expense management, and risk platforms
- Leverage AI tools and techniques
- (e.g., code-generation assistants, LLM-powered automation, prompt engineering, Spec-Driven Development) to accelerate development, improve code quality, and enhance platform capabilities
- Contribute to the design and development of AI-driven and agentic solutions including intelligent workflows, retrieval-augmented generation (RAG) pipelines, and automated decision-support systems
- Collaborate globally with sponsors, users, and engineering colleagues across multiple divisions to create end-to-end solutions that meet complex business requirements
- Participate in code reviews to ensure quality, maintainability, and adherence to engineering best practices
- Take technical ownership of features and components, managing multiple stakeholders and driving delivery within a global team
- Stay current with the latest advancements in AI/ML platforms, tools, and software engineering practices to continuously improve our solutions

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