Engineering Manager, Software Engineering (AI/LLM Platform)

Quick Facts

• Role: Engineering Manager responsible for delivery of shared AI capabilities across an enterprise platform

Description

Lead engineering execution and technical direction for AI-powered solutions that enhance how legal professionals work. Partner with Product and Architecture to convert customer needs and emerging AI technologies into scalable, secure, and reliable product capabilities, with a strong focus on LLM/RAG evaluation, testing, and monitoring. Coach and develop a team of software engineers and drive cross-functional alignment to deliver high-quality AI experiences.

Responsibilities

• Plan and execute engineering initiatives for predictable delivery of high-quality AI capabilities

• Translate customer needs and AI technologies into scalable and secure solutions

• Balance feature delivery with reliability, performance, cost efficiency, and operational excellence

• Identify technical risks, dependencies, and tradeoffs; communicate recommendations to stakeholders

• Guide AI technical strategy and architecture with Principal/Staff Engineers

• Evaluate model selection tradeoffs (quality, latency, scalability, cost)

• Lead prompt engineering and RAG approaches for accurate, contextually relevant results

• Define expectations for AI evaluation, testing, and monitoring (including regression testing)

• Ensure enterprise standards for security, privacy, compliance, and reliability

• Provide technical leadership using C#/.NET, microservices, containerization, and AWS or Azure

• Lead, coach, and develop engineering talent; drive hiring and continuous improvement

• Align with Product, Design, Architecture, and other AI teams on shared platform capabilities

• Communicate progress, technical decisions, risks, and tradeoffs clearly to leadership

Requirements

• 6+ years of professional software engineering experience; 2+ years managing engineering teams

• Production experience delivering AI/LLM-powered features in an enterprise SaaS environment

• Strong understanding of LLMs including prompt engineering, RAG, context limitations, latency, cost, and failure modes

• Familiarity with AI evaluation methodologies and retrieval systems

• Knowledge of AI agent architectures and tool-calling patterns, including Model Context Protocol (MCP)

• Solid foundation in distributed systems, microservices, and cloud-native architectures

• Experience with AWS or Azure, CI/CD, containerization, and observability

• Working knowledge of C#/.NET to evaluate designs and guide engineering decisions

• Demonstrated ability to lead teams and deliver complex technical initiatives

• Strong communication, collaboration, and stakeholder management skills

• Bachelor’s degree in CS/Engineering (or equivalent practical experience)

Benefits

• Company-covered healthcare premiums: 90%

• HSA company contribution

• 401(k) match at 4% with immediate vesting

• Flexible PTO (typically 3–4 weeks/year)

• 10 paid holidays

• Monthly contributions for life activities & wellness

• Monthly dedicated time for LinkedIn Learning

• Mentorship and access to leadership

• Opportunities for advancement in a growing company

• Compensation transparency: $170,000–$190,000 (on-target earnings)