Engineering-L2-Hyderabad-Vice President-Software Engineering

Posted 11 Days Ago
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Hyderabad, Telangana, IND
In-Office
Expert/Leader
Fintech • Financial Services
The Role
Build and deploy production multi-agent (LLM) systems to autonomously plan, reason, and execute across distributed cloud environments. Design agentic substrate, integrate agents with humans and firm APIs, optimize compute infrastructure, improve observability, and incubate agent-driven workflows with business partners.
Summary Generated by Built In

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.  Create new businesses, transform finance, and explore a world of opportunity at the speed of markets. Goldman Sachs Engineers are innovators and problem-solvers, building solutions in Artificial Intelligence, risk management, big data, mobile and more.

We are seeking entrepreneurial Agentic Software Engineers to join a newly formed AI Agentic Systems team. This team is tasked with solving firmwide, large-scale compute infrastructure challenges by architecting and deploying autonomous "swarms" of agents. These agents will interface seamlessly with human teams, and complex digital substrates to optimize, analyze, and manage our global technology footprint.

As a founding member of this team, you will help incubate a new paradigm of software engineering—moving beyond static automation to dynamic, goal-oriented agentic systems that operate across the totality of the firm’s business units.

Key Responsibilities 

  • Agentic Orchestration: Design and deploy multi-agent systems (swarms) capable of autonomous planning, reasoning, and execution across distributed cloud environments.

  • System Integration: Build robust interfaces between AI agents, and human stakeholders to ensure high-fidelity feedback loops and operational transparency.

  • Infrastructure at Scale: Develop agentic solutions for complex compute infrastructure problems, including real-time observability, predictive optimization, and automated capacity planning.

  • Substrate Development: Contribute to the "agentic substrate"—the underlying platform and tooling that allows agents to securely access data, execute code, and interact with firmwide APIs.

  • Cross-Functional Incubation: Partner with diverse business units to identify high-impact use cases for agents, translating ambiguous business needs into technical agentic workflows.

Required Qualifications

  • Software Engineering Excellence: Strong proficiency in Python, Go, or C++ with a deep understanding of distributed systems and cloud-native architecture (AWS, Azure, or internal private clouds).

  • Agentic Experience: Direct experience deploying LLM-based agents in production environments. Familiarity with frameworks such as LangGraph, AutoGPT, or custom-built orchestration layers.

  • Problem-Solving Domains: Proven track record of applying agentic patterns to at least two of the following:

    • Data Analysis: Autonomous synthesis of large-scale datasets.

    • Observability: Self-healing infrastructure and automated root-cause analysis.

    • Optimization: Dynamic resource allocation and cost management.

    • Planning: Multi-step task decomposition and execution in non-deterministic environments.

  • Entrepreneurial Mindset: Ability to thrive in a 0-to-1 environment, comfortable with ambiguity, and driven to build systems that have never existed before.

Preferred Skills

  • Experience with Digital Twin technology and its integration with real-time telemetry.

  • Knowledge of Multi-Agent Reinforcement Learning (MARL) or swarm intelligence principles.

  • Familiarity with Model Context Protocol (MCP) and other emerging standards for agent-to-tool communication.

  • Strong communication skills to bridge the gap between technical agentic logic and human-centric business processes.

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 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 several 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 accommodation for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

Skills Required

  • Proficiency in Python, Go, or C++
  • Deep understanding of distributed systems and cloud-native architecture (AWS, Azure, or private clouds)
  • Direct experience deploying LLM-based agents in production environments
  • Familiarity with agent orchestration frameworks such as LangGraph, AutoGPT, or custom-built orchestration layers
  • Proven track record applying agentic patterns to at least two domains (data analysis, observability, optimization, planning)
  • Ability to operate in a 0-to-1, ambiguous, entrepreneurial environment
  • Experience with Digital Twin technology and real-time telemetry
  • Knowledge of Multi-Agent Reinforcement Learning (MARL) or swarm intelligence principles
  • Familiarity with Model Context Protocol (MCP) and agent-to-tool communication standards
  • Strong communication skills to bridge technical agent logic and business processes

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

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The Company
HQ: New York, NY
67,118 Employees

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

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