Software Engineers

This role is ideal for an engineer who enjoys building products and services for other developers: someone equally comfortable standing up a new service, tracing a request across the platform to determine why it was slow, figuring out why a container works locally and fails on the host, and replacing a manual deployment step with a pipeline. You will work closely with engineers who own the platform layer and developers who build on it., * Platform Ownership: Design, build, and operate the systems and shared infrastructure that AI applications at the firm depend on.

• Observability & Reliability: Own metrics, logs, and traces for the platform. Instrument services, build dashboards and alerts, and use telemetry to diagnose and resolve performance and reliability issues.
• Hardening & Operations: Improve the resilience, security posture, and operational maturity of existing systems.
• Developer Enablement: Provide the tooling, environments, and deployment paths that let application developers ship AI agents and workflows onto the platform quickly and safely. Treat internal developers as your users.
• Collaboration: Partner with engineers, data scientists, product managers, and corporate departments (Security, IT) to understand requirements, communicate tradeoffs, and deliver platform capabilities that fit how the firm works.

• Experience: BA/BS with 4+ years of professional software, platform, infrastructure, or DevOps engineering experience, OR a Master or PhD in a quantitative field (e.g., Computer Science, Math, Economics) with 2+ years of industry experience.
• Engineering Mindset: Strong fundamentals in system design, with the ability to build reliable systems that handle sensitive data with high reliability.
• Technical Versatility: Demonstrated ability to work across tech stacks and pick up new languages or frameworks quickly
• AI-Native Development: Experience using AI-powered coding assistants to accelerate development; strong interest in staying at the forefront of AI-enabled engineering.
• Agentic Tooling: Familiarity with building AI agents (e.g., using the Claude Agent SDK), and with what it takes to run agents safely in sandboxed environments.
• Containers: Deep, practical experience with environment isolation concepts and container solutions such as Docker, Podman, or Bubblewrap
• Observability: Hands-on experience with metrics, logging, and distributed tracing, ideally with the Grafana ecosystem (Grafana, Loki, Tempo, Mimir, Alloy) and OpenTelemetry.
• Communication: Ability to clearly articulate technical tradeoffs, document systems well, and explain progress to both technical peers and non-technical stakeholders.

Preferred

• Reverse Proxies & Gateways: Experience configuring and operating reverse proxies or API gateways (e.g., Nginx): routing, TLS, authentication, rate limiting, and request/response handling.

• Networking & Service Connectivity: Solid grasp of how services find and talk to each other across hosts and networks, including HTTP, gRPC, and similar protocols, TCP and TLS, DNS and service discovery, ports and subnets.

• CI/CD & Infrastructure as Code: Experience with GitLab CI or similar pipelines, and with infrastructure-as-code or configuration management tools (e.g., Terraform, Ansible).
• Orchestration: Exposure to Kubernetes or similar orchestration systems, and an informed view on when they are and are not the right tool.
• Hybrid Environments: Experience operating across on-premises and cloud infrastructure.
• Identity & Secrets: Familiarity with SSO/OIDC, identity and access management, secrets management, and audit logging.
• Regulated or Professional Services Environments: Experience building infrastructure within professional services, legal, financial, or highly regulated industries.

Cornerstone Research is at the forefront of economic and financial consulting, delivering the rigorous analytical solutions required to navigate complex disputes. The firm draws from an extensive network of prominent academic and industry experts to support each matter effectively. Pairing a deep understanding of economics and finance with a suite of industry-leading artificial intelligence and machine learning tools, Cornerstone provides clients with a sophisticated, tailored approach. A reputation for innovation, precision, and excellence has defined Cornerstone since 1989. That momentum continues with over 1,000 professionals collaborating across nine offices in the US, UK, and EU., The Data Science Center (DSC) is the Cornerstone Research’s center of excellence for advanced analytics, data infrastructure, and AI-enabled innovation. The DSC sits at the intersection of economics, data science, and litigation. We partner with consultants to build practical, AI-powered products that reshape how Cornerstone delivers. The DSC brings together deep domain expertise, direct access to real user problems, and strong distribution channels, creating the conditions for legal technology that lasts.