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About This Role
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.
Your Impact
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 application and infrastructure challenges by building and deploying swarms of agents. You will build systems that understand, plan, transform, and validate application modernization workflows across one of the largest and most complex technology estates in the industry.
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 all 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.
- Learning and Feedback: Build human-in-the-loop systems, evaluation frameworks, and observability mechanisms that enable continuous agent improvement.
- Tool Integration: Design and build integrations with APIs, developer tooling, CI/CD pipelines, data platforms, or operational systems.
- Cross-Functional Collaboration: Partner with diverse business units to identify high-impact use cases for agents, translating ambiguous business needs into technical agentic workflows.
Basic Qualifications:
- Software Engineering Excellence: Strong proficiency in Python, Go, Java, Javascript or similar languages with a deep understanding of distributed systems and cloud-native architecture (AWS, Azure, or internal private clouds).
- Agentic Experience: Direct experience deploying and operating LLM-based agents in production environments. Familiarity with frameworks such as LangGraph, AutoGPT, or custom-built orchestration layers.
- AI Evals: Experience designing benchmarks, evaluations, and quality metrics for AI systems.
- 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 Qualifications:
- Demonstrated interest in emerging agentic technologies such as Multi-Agent Reinforcement Learning (MARL), and swarm intelligence, with a willingness to experiment, learn, and apply new approaches where they create practical business value.
- Familiarity with Model Context Protocol (MCP), A2A 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. 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. : https://www.goldmansachs.com/careers/footer/disability-statement.html
We Offer Best-In-Class Benefits Healthcare & Medical Insurance We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance. Holiday & Vacation Policies We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year. Financial Wellness & Retirement We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees’ priorities. Health Services We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state-of-the-art on-site health centers in certain offices. Fitness To encourage employees to live a healthy and active lifestyle, some of our offices feature on-site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre-approved amount). Child Care & Family Care We offer on-site child care centers that provide full-time and emergency back-up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available. Benefits at Goldman Sachs Read more about the full suite of class-leading benefits our firm has to offer.
Opportunity Overview CORPORATE TITLEVice President OFFICE LOCATION(S)Seattle JOB FUNCTIONSoftware Engineering DIVISIONEngineering Division SALARY RANGEUSD 150,000 - 250,000
Salary Context
This $150K-$250K range is above the median for AI Software Engineer roles in our dataset (median: $193K across 172 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,653 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Goldman Sachs, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,448 positions with disclosed compensation. This role's midpoint ($200K) sits 9% below the category median. Disclosed range: $150K to $250K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Goldman Sachs AI Hiring
Goldman Sachs has 14 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Product Manager, AI Safety. Positions span London, England, UK, Shanghai, Shanghai, China, Seattle, WA, US. Compensation range: $250K - $250K.
Location Context
AI roles in Seattle pay a median of $226,100 across 973 tracked positions. That's 6% above the national median.
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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