Software Engineer – AI Platform

Responsibilities

• Own backend and AI orchestration systems powering AI agents, conversations, work spaces, and knowledge bases across CoCounsel for Audit
• Define patterns for MCP servers, agent design, novel LLM uses, experimentation, and scalable infrastructure
• Shape platform integration strategy across new and existing Thomson Reuters audit systems
• Build and evolve systems operating over millions of documents, structured tax data, changing laws, and thousands of concurrent AI interactions
• Lead multi-quarter initiatives across AI, product, and infrastructure
• Mentor senior and mid-level engineers on system design, code quality, and AI integration
• Collaborate with AI/ML engineers, researchers, designers, and product managers
• Help shape the roadmap, technical strategy, engineering culture, experimentation, testing, rollout, and postmortems
• Architect and implement backend services using Python, FastAPI, PostgreSQL, AWS, and Vercel
• Build AI orchestration involving routing, tool calling, MCP servers, multi-step workflows, safety, guardrails, and third‑party LLM error handling
• Design high‑throughput, low‑latency AI workloads using caching, queuing, rate‑limiting, model failover, and cost/performance trade‑offs
• Work with large‑scale data, retrieval and search, vector stores, and indexing strategies
• Establish and refine SLOs, observability, and incident response for correct, auditable, and trustworthy AI systems

• Bachelor’s degree in computer science, Computer Engineering, a related field, or equivalent experience
• 5-7+ years of experience in full-stack development, building scalable cloud-based applications, web services, APIs and AI-driven products
• Deep Python expertise
• Production systems experience using FastAPI or similar frameworks
• Experience with relational databases such as PostgreSQL or equivalent
• Experience with a major cloud provider, AWS preferred
• Strong background in distributed systems, data modeling, API contracts, observability, resilience patterns, and performance tuning under load
• Proven track record leading large, complex projects end‑to‑end: architecture, execution, rollout, and long‑term operation
• Excellent communication skills and ability to partner with product, design, and ML teams
• Demonstrated interest in AI systems and engineering paradigms including LLMs, agents, and retrieval
• Hands‑on experience integrating LLM APIs such as OpenAI and Anthropic into production applications, including prompt/response management, cost controls, and safety considerations
• Experience with vector databases, embeddings, semantic search, or custom retrieval pipelines
• Experience with automated testing, reliability, and release practices for systems with non-deterministic model behavior
• Experience in correctness-, auditability-, and compliance-sensitive domains such as fintech, tax, audit, or legal, or strong interest in applying AI in those contexts

Demonstrates expertise in backend development and AI orchestration, with a strong focus on Python, FastAPI, and scalable cloud-based applications. Proven ability to lead complex projects, mentor engineers, and collaborate effectively across multidisciplinary teams.

• Deep Python Expertise
• Production Systems Experience Using FastAPI
• Experience With AWS
• Strong Background In Distributed Systems
• Hands‑On Experience Integrating LLM APIs

• Backend Development
• AI Orchestration
• Full-Stack Development
• Scalable Cloud-Based Applications
• Web Services
• APIs
• Data Modeling
• Automated Testing
• Performance Tuning
• Incident Response

• Excellent Communication Skills
• Mentoring
• Collaboration

• Bachelor’s Degree In Computer Science

• AI Systems
• LLMs
• Audit
• Fintech
• Tax
• Legal

• FastAPI
• PostgreSQL
• AWS
• Vercel
• Vector Databases
• OpenAI API
• Anthropic API