Investment Engineer

Bridgewater Associates • New York, NY

10h • $225,000 - $450,000 • Onsite

About The Position

Bridgewater has been pursuing the idea that the world can be understood through cause-and-effect relationships in markets and economies. They aim to generate uncorrelated returns by understanding and navigating macroeconomic shifts. Their approach involves building a System, which is code and algorithms that ingest data and reflect learned relationships to generate views automatically. This requires human-machine collaboration, with a vision of an artificial investor. Bridgewater has introduced AIA (Artificial Investment Associate), a fully machine-powered investing strategy, and is transforming human investors' jobs through AI. The company emphasizes intense collaboration between brilliant people, without ego or politics, to arrive at the best ideas and rapidly elevate strong thinkers.

Investment Engineers are crucial in making Bridgewater's investment ideas a reality by running systems. They act as engineers, architects, and toolmakers, designing, implementing, and scaling the technology that translates research insights into daily investment decisions across global markets. The role seeks individuals with strong software engineering and systems backgrounds in computer science, machine learning engineering, distributed systems, or data engineering, who are eager to apply their skills to complex problems in finance.

Requirements

• Strong software engineering fundamentals, including data structures, algorithms, and system design.
• A track record of building and shipping production systems.
• Several years of professional experience in software engineering, infrastructure, data engineering, or ML engineering in a demanding environment (technology, finance, etc.).
• Proficiency in one or more languages commonly used in quantitative systems (e.g., Python, Java, C++).
• Comfort picking up new tools quickly.
• Experience designing systems that handle complex data processing, real-time or near-real-time workloads, or high-reliability requirements.
• A strong interest in financial markets, economics, or quantitative investing.
• A collaborative, low-ego working style.
• A drive to grow rapidly through direct feedback and hard problems.
• Eligibility to work in the United States for a minimum of 3 years from the start date.
• If visa sponsorship is required, continuous or eligible-to-renew work authorization in the United States for at least three years without lottery selection.

Nice To Haves

• You don't wait for a roadmap; you build the first version yourself.
• Your inventiveness is grounded in real engineering discipline—you know that production-grade craft is what separates a clever prototype from lasting edge.
• You stay close to the leading edge of software engineering, data infrastructure, and machine learning tooling.
• You evaluate new technologies with a sharp eye—not chasing hype, but recognizing when a new framework, paradigm, or platform can meaningfully improve how we build.
• You understand investment logic well enough to implement it faithfully, spot when something doesn't look right, and ask hard engineering questions.
• You know that the gap between 'works in research' and 'works in production' is where most value is created—or destroyed.
• You bring rigor to every stage of the development lifecycle—from scoping and design through testing and deployment.
• You know when to build for durability and when to prototype for speed, and you communicate those tradeoffs clearly.
• You don't gold-plate, but you also don't ship fragile systems into environments where reliability matters enormously.
• You translate fluently between engineers, researchers, and investors—turning abstract investment questions into concrete system requirements, and surfacing technical constraints.
• You give and receive direct feedback without defensiveness, and you care more about the outcome than about who gets credit.
• You want to understand why a system is built a certain way, what the investment logic is trying to capture, and how the markets it touches actually behave.
• That curiosity makes you a far better engineer—and over time, a more complete contributor to the investment process.

Responsibilities

• Design, build, and own the systems that power Bridgewater's investment process, including algorithms that process global economic data into market views and trades.
• Architect and implement systems ensuring performance, reliability, testability, and adaptability to evolving investment thinking.
• Bridge the gap between research and production by turning investment ideas, models, and analytical frameworks into robust, production-grade systems.
• Work closely with researchers to understand intent, design clean abstractions, build thorough test harnesses, and ensure production systems accurately reflect research designs.
• Build and evolve the technology platform, investing in shared infrastructure, tooling, and frameworks like data pipelines, execution systems, monitoring, observability, and backtesting frameworks.
• Evaluate and integrate emerging technologies like AI-native development tools and large language models to improve development velocity, system quality, or enable new capabilities.
• Operate, monitor, and continuously improve live systems that trade global markets daily, ensuring operational health and rapid resolution of issues.
• Use production behavior as a feedback loop to identify improvements in both technology and underlying investment logic.

Benefits

• Competitive suite of benefits.
• The total compensation range across these roles is $225,000–$450,000 inclusive of base salary and discretionary target bonus.
• The expected base salary is typically 50%–75% of the relevant range, depending on team, level, and experience.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed