The Conflicts Resolution Group (CRG) is a control function with a primary objective to identify and mitigate the firm’s actual or perceived conflicts of interest and associated reputational risks which may result from the firm taking on a new role, responsibility, or position on a potential deal or with a potential counterparty. CRG Engineering plays a critical role in the development and support of software solutions aligned with the CRG objectives for improved risk management for the firm and ensuring a timely turnaround for our revenue divisions.

• Partner globally across CRG and other Engineering teams to design and deliver end-to-end AI-enabled platforms.
• Design, develop, test, deploy, and maintain services with a strong emphasis on AI/GenAI use cases.
• Build scalable data processing, workflow, and API solutions across large datasets, real-time processing, and event-driven architectures.
• Collaborate in an agile environment with product, legal, data science, and design partners to prototype ideas and share best practices.
• Demonstrate willingness to learn, support, and modernize legacy systems that underpin critical conflicts resolution business processes.
• Apply modern AI techniques—including LLMs, RAG, and agent-based frameworks—to solve business and risk-management problems.

• Strong programming experience in Java and Python.
• Hands-on experience applying LLMs, prompt engineering, RAG, and AI agents to real-world problems.
• Strong analytical and problem-solving skills, with the ability to translate complex business and regulatory requirements into technical solutions.
• Experience with data stores and search technologies (e.g., SQL, MongoDB, Elastic) and familiarity with distributed or real-time systems (e.g., Kafka).
• Experience building AI agents, including tool use, planning, and orchestration.
• Experience building and deploying cloud-native services on an AWS stack, with strong grounding in automated testing, SDLC practices, and CI/CD pipelines.
• Excellent communication and collaboration skills across technical and non-technical stakeholders.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field.
• 0–3+ years of relevant professional software engineering experience, depending on level.
• Experience in some of the following is desired and can set you apart from other candidates:
• Experience with agent and RAG frameworks such as LangChain, LangGraph, and/or ADK.
• Frontend experience with React/Angular.
• Familiarity with platforms and tooling such as GitLab and Kubernetes.
• Knowledge of financial services or control functions such as legal, compliance, or risk management.