Forward Deployed Engineer

About the role

As a Forward Deployed Engineer on the Koch Risk Optimization team, you will serve as an embedded technical partner and full-stack builder who creates production-ready applications, data analytics solutions, and generative AI workflows to solve complex risk, financial, and investment challenges. You will collaborate directly with risk capability leaders, quantitative analysts, and technology support groups to rapidly prototype, deploy, and own high-impact technical solutions across market risk, credit risk, insurance and investments domains. If you are an entrepreneurial builder who leverages AI-assisted development tools daily to multiply your engineering velocity and wants direct ownership of mission-critical systems and solutions, this role offers an unmatched platform to create value. Koch Risk Optimization creates long-term value by driving risk-adjusted decision making, capital allocation, and risk absorption across Koch companies globally. The team partners with commercial, trading, insurance, treasury and investment capabilities to optimize portfolio risk-return outcomes, fostering an entrepreneurial, high-agency environment that pairs deep domain expertise with cutting-edge technology to turn complex market and financial uncertainties into strategic advantage.

Responsibilities

• Work side‑by‑side with domain experts to build, deploy, operate, and improve systems that support risk/reward optimization for significant commercial, trading, and capital allocation activities across Koch.
• Take the lead on requirements gathering, prototyping, full‑stack development and follow‑through to deliver useful analytics, applications and AI solutions that result in better decisions.
• Work across teams to enhance operational outcomes: connect and collaborate with existing technical support resources to augment your capabilities, fostering partnerships based on mutual benefit and comparative advantage; drive towards a common goal of maintaining stable and reliable performance for applications and systems used by the Risk Optimization team.
• Lead AI‑native engineering practices to enhance the team’s execution speed and expand capabilities: champion AI‑native software engineering methodologies to accelerate output and expand technical operational range across the team; partner with Risk Optimization team members to contribute additional expertise towards development and deployment of models and analytics so the team can be more responsive to business needs.
• Develop and support innovative Gen AI workflows and agents: the Risk Optimization team has deployed numerous Gen AI solutions across the enterprise, with an active project pipeline; you will play an integral role in the strategy to lead on the frontier of generative AI at Koch.
• Uphold enterprise architecture standards: collaborate with enterprise architecture leaders and support groups to maintain robust identity, security, data and platform governance standards across all deployed systems.

Requirements

• Professional experience in both front‑end and back‑end software engineering.
• Experience building, deploying, and operating applications in an enterprise cloud environment (e.g., AWS, Azure, GCP).
• Experience using AI‑native developer tooling (e.g., Claude Code, Cursor, GitHub Copilot, etc.), to accelerate software design, implementation, and refactoring while carefully managing the quality and maintainability of outputs.
• Experience directly collaborating with business stakeholders and end users to translate business requirements into working software solutions.
• Strong proficiency in modern programming languages and web stacks (e.g., Python, TypeScript/JavaScript, modern frontend frameworks, SQL).
• Experience supporting & maintaining applications in production.
• Interest and excitement for learning about financial markets, investments, and commodities trading.

Qualifications

• Experience operating as an embedded engineer within a business unit or trading/investment environment with high autonomy and direct decision rights.
• Willingness to learn unfamiliar systems and business areas and collaborate with other groups to accomplish complex goals.
• Experience designing and implementing generative AI workflows, skills, and agents.
• Experience designing and deploying end‑to‑end data pipelines and database architectures (relational, document, or cloud data warehouses), including experience