AI Engineer

We’re looking for an experienced AI Engineer to join Optiver’s Applied AI and Platform Engineering team. In this role, you’ll design, build, and deploy production-grade AI systems that automate workflows, augment decision-making, and accelerate engineering across the firm. You’ll own the full lifecycle—from identifying opportunities and translating ambiguous business problems into scalable AI solutions to deploying, operating, and continuously improving systems in production. You’ll combine strong software engineering with pragmatic AI expertise to build reliable AI products that deliver measurable business impact.

What you’ll do

As an AI Engineer, you will:

• Design, build, and deploy production-grade AI systems and products—including agent platforms, AI assistants, code review harnesses, evaluation frameworks, and agentic research pipelines—using Python and modern AI frameworks integrated with internal systems, data platforms, and third-party AI services.
• Evaluate foundation models, agent architectures, and AI workflows, making pragmatic technology decisions based on capability, reliability, latency, security, cost, and business impact.
• Define success metrics and build robust evaluation frameworks, benchmarking tools, and observability capabilities to measure AI quality, safety, performance, and production readiness while enabling continuous improvement.
• Translate ambiguous business challenges into scalable technical solutions, ensuring AI-assisted development produces reliable software that meets both functional requirements and business objectives.
• Design resilient, distributed AI systems with a focus on scalability, state management, authentication, fault tolerance, security, and operational reliability.
• Rapidly prototype and experiment with emerging models, tools, and workflows, validating new capabilities against measurable success criteria before investing in production.
• Partner closely with trading, research, and business teams to understand user needs, challenge assumptions, rapidly iterate on solutions, and evolve successful use cases into reusable platform capabilities.
• Deliver high-quality, maintainable software through sound software engineering practices, automated testing, and thoughtful code reviews.
• Operate, monitor, and continuously improve production AI systems by optimizing quality, reliability, latency, cost efficiency, governance, and user outcomes.

What you’ll get

You’ll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by continuous improvement, you’ll thrive in a supportive, high-performing environment while tackling some of the toughest technical challenges in the financial markets.

In addition, you’ll receive:

• The opportunity to work alongside world-class engineers and researchers from more than 40 countries
• A highly competitive compensation package, including a performance-based bonus
• A 401(k) match of up to 50%
• Comprehensive medical, dental, vision, mental health, disability, and life insurance
• 25 days of paid vacation, plus market holidays
• Extensive office perks, including breakfast, lunch, snacks, social events, clubs, sports leagues, and more

Who you are

• Bachelor’s degree in Computer Science, Artificial Intelligence, or a related technical field
• 6+ years of professional software engineering experience, including extensive production experience developing applications in Python
• Strong software engineering fundamentals, including software architecture, object-oriented design, design patterns, distributed systems, testing, and building scalable, resilient applications
• Experience designing, deploying, and operating production LLM applications, with practical knowledge of model evaluation, prompt engineering, tool calling, context management, agent orchestration, and common failure modes
• Experience defining evaluation frameworks and using quantitative metrics to guide model selection, prompt iteration, and production readiness
• Experience integrating AI systems with external tools, APIs, Model Context Protocol (MCP), and modern AI application frameworks
• Strong engineering judgment, with the ability to determine when AI is the right solution—and when traditional software or deterministic automation is more appropriate
• Experience building highly reliable production systems where correctness, resiliency, observability, and operational excellence are essential…