Principal Engineer, CoCounsel

About the role

As a Principal Software Engineer, you will set the technical direction for the backend, AI orchestration, and identity systems that turn frontier models into reliable, secure, production-grade workflows that attorneys, in-house legal departments, and government agencies trust on real client matters every day. This role sits at the heart of the CoCounsel Legal engineering organization, partnering closely with AI/ML engineers, researchers, product, and our identity and platform teams to deliver world-class legal content and AI experiences at scale.

Responsibilities

• Participate in shaping the company’s AI platform and patterns: Define patterns for building MCP servers, designing agents, novel uses of LLMs, experimentation, and scalable infrastructure.
• Work at real production scale: Build and evolve systems that operate over millions of documents, complex and ever-changing law, privileged client data, and thousands of concurrent AI interactions from professionals doing time-sensitive work.
• Join a tight group of senior engineers and researchers shipping quickly, with direct access to product leadership and customers.
• Lead and/or design initiatives that cut across AI, product, identity, and infrastructure.
• Mentor staff and senior engineers, raising the bar on AI integration practices, system design, code quality, and security across the org.
• Help shape the team’s roadmap, technical strategy, and engineering culture – from experimentation practices to testing, rollout, and postmortems.
• Help define and lead the platform integration strategy across new and existing Thomson Reuters legal systems to deliver world-class content and solutions for our customers.
• Define how autonomous agents act on a user’s behalf safely: scoped delegation, least-privilege service identities, secrets management, and consistent enforcement of entitlements across documents, matters, and content repositories.
• Partner with security, platform, and compliance teams on multi-tenancy isolation, data residency, privilege protection, and the audit trails that legal and government customers require.
• Design for high-throughput, low-latency AI workloads: caching, queuing, rate-limiting, model failover, and cost/performance trade-offs.
• Work with large-scale data: millions of documents, retrieval and search, vector stores, and indexing strategies tailored to legal use cases.
• Establish and refine SLOs, observability, and incident response for AI systems that must be correct, auditable, and trustworthy in professional legal workflows.

Requirements

• Bachelor’s Degree in Computer Science, Computer Engineering, a related field, or equivalent experience.
• Demonstrated experience building with AI – LLMs, agents, and retrieval – and a strong point of view on what “AI-native” software should look like.
• Proven track record owning large, complex projects end-to-end: architecture, execution, rollout, and long-term operation.
• Deep Python expertise and experience with production systems using frameworks like FastAPI (or similar), relational databases (PostgreSQL or equivalent), and a major cloud provider (AWS preferred).
• Strong background in distributed systems: data modeling, API contracts, observability, resilience patterns, and performance tuning under load.
• Hands-on experience with identity and access management – designing or integrating authentication and authorization at scale (SSO, SAML, OIDC, OAuth 2.0, RBAC/ABAC, token/session management, or comparable IAM systems).
• Excellent communication skills and the ability to partner with product, design, security, and ML teams in a fast-moving environment.

Qualifications

• Preferred Skills & Experience:
• Hands-on experience designing and operating agentic systems in production – tool calling, MCP servers, multi-step workflows, and orchestration around third-party and in-house LLMs (e.g., Anthropic, OpenAI), including prompt/response management, cost controls, and safety considerations.
• Experience with AI-adjacent infrastructure: vector databases, embeddings, semantic search, or custom retrieval pipelines.
• Opinions and experience around automated testing, reliability, and release practices for systems with non-deterministic model behavior.

Skills

• Python
• FastAPI
• Relational databases (PostgreSQL or equivalent)
• AWS
• Distributed systems
• Identity and access management
• Communication

Benefits

• Hybrid Work Model
• Flexibility & Work-Life Balance
• Career Development and Growth
• Industry Competitive Benefits
• Culture
• Social Impact
• Make a Real-World Impact

Pay

$158,900 USD - $295,100 USD

Schedule

Hybrid Work Model