Engineering Manager, AI Platform

Job Summary

Epiq supports some of the world’s largest and most complex legal matters, where document collections can range from thousands to millions of records. As an Engineering Manager, AI Agents & Accelerators, you will lead a high-performing engineering team responsible for building intelligent AI-powered solutions that transform how legal professionals interact with and analyze data at scale.

You will oversee the development and delivery of two strategic product areas: AI Agents and AI Accelerators.

AI Agents

Intelligent, conversational systems that enable legal professionals to ask complex questions in natural language and receive accurate, evidence-based responses grounded in case data. These agents leverage advanced retrieval, reasoning, orchestration, tool integration, and citation capabilities to support legal workflows with transparency and trust.

AI Accelerators

AI-powered workflows and models designed to automate and streamline large-scale document review and analysis. These solutions assist with tasks such as responsiveness classification, privilege identification, PII/PHI detection, summarization, translation, transcription, entity extraction, timeline generation, and other review-intensive activities.

The ultimate goal is to help legal teams reach defensible outcomes faster, improve review efficiency, and reduce overall litigation and investigation costs while maintaining the highest standards of quality and accountability.

This is a hands-on engineering leadership role. You will be accountable for team performance, technical excellence, product delivery, and operational outcomes. While your primary focus will be leading engineers, you are expected to engage deeply in architectural decisions, engineering reviews, evaluation strategies, and technology direction.

Key Responsibilities

Team Leadership & Talent Development

• Hire, mentor, coach, and grow a multidisciplinary team of software, data, and AI engineers.
• Foster a culture of innovation, collaboration, continuous learning, and engineering excellence.
• Support career development, technical growth, and high-performance execution across the team.

Product & Platform Delivery

• Lead the end-to-end development of AI agent capabilities, including orchestration frameworks, retrieval systems, tool integrations, and conversational user experiences.
• Drive delivery of AI accelerators from concept through production deployment, ensuring scalability, reliability, and measurable business impact.
• Partner closely with Product Management, Legal Domain Experts, Review Operations, and Engineering stakeholders to execute a shared roadmap.

AI Quality & Evaluation

• Establish and maintain robust evaluation frameworks and quality standards.
• Define metrics and processes for measuring accuracy, grounding, citation quality, relevance, and system reliability.
• Implement testing and regression strategies to validate prompt, workflow, and model updates before release.

Governance & Responsible AI

• Define operational guardrails and decision boundaries for AI-enabled workflows.
• Establish clear escalation and human-in-the-loop processes for cases requiring human review or approval.
• Ensure solutions align with security, compliance, legal, and responsible AI requirements.

Performance & Scalability

• Optimize system performance across both real-time and batch-processing workloads.
• Drive architectural decisions related to model routing, retrieval strategies, inference optimization, caching, batching, and cost management.
• Balance latency, throughput, quality, and operational efficiency across large-scale deployments.

Technical Leadership

• Provide guidance on architecture, design patterns, engineering best practices, and technology strategy.
• Participate in design reviews, code reviews, technical planning, and operational readiness activities.
• Partner with global engineering leaders to drive consistency and innovation across the platform.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience.
• 3+ years of people management experience leading software engineering teams.
• Strong background in software engineering with experience delivering scalable, production-grade applications and platforms.
• Experience building and delivering customer-facing products where performance, reliability, …