Senior Director, Software Engineering – Data & AI Platforms

Epiq, the world’s leading Legal Solutions provider, is changing the legal tech game. We are looking for a Senior Director, Software Engineering – Data & AI Platforms to expand data and information management capabilities across our organization.

The successful candidate will help deliver our vision for our Data & AI Platforms, working directly under the CTO, together with Product Management, Operations, AI/ML, and other stakeholders in the organization. The person will be a thought leader driving the Software Development function along with the Data Integration/Data Quality initiatives of the Epiq Service Cloud, including the data foundations that power our AI and GenAI capabilities, and a tremendous team player who builds connections across the organization.

This is still a hands-on role, so we are looking for someone who can not only set our vision to advance this capability but also help implement it, leading a team of 80- 100 people based primarily in India. The team is using a cloud-native, modern technology stack built on AWS, Microsoft Azure, Snowflake, Kubernetes, and PowerBI, with growing investment in streaming, Lakehouse, and GenAI/vector infrastructure, among other things.

Responsibilities

• Demonstrated hands-on software engineering background (e.g., Python, Scala, or Java), with a track record of personally writing, reviewing, and shipping production-grade code, not solely directing the work of others.
• Solid grounding in core engineering practices: version control (Git), CI/CD pipelines, automated testing, and formal code review standards.
• Experience designing and building APIs, services, and event-driven/ microservices architectures that other engineering and product teams build on top of.
• Working knowledge of infrastructure-as-code (e.g., Terraform, CloudFormation) and containerized deployment (Docker/Kubernetes) from an ownership and architecture standpoint, not just as a consumer.
• Familiarity with secure software development lifecycle (SDLC) practices , dependency management, secrets management, and security review , particularly relevant given the sensitivity of legal data.
• Experience architecting for reliability and scale: observability (logging, monitoring, alerting), incident response, and performance/cost tuning of production data services.
• Develop a critical understanding of business data to proactively identify opportunities to improve data quality and deliver solutions and insights. Partner with AI/ML and Product teams to build the data foundations (pipelines, feature stores, vector search, RAG-ready datasets) that power our GenAI and agentic product capabilities.
• Provide guidance for data integrity issues, ongoing maintenance, and data governance, including responsible-AI data practices such as lineage tracking and PII/PHI handling appropriate for legal data.
• Maintain detailed documentation of data collection methods and dependencies.
• Work with key stakeholders to understand BI/Analytics and reporting requirements.
• Conduct audits and troubleshoot tracking gaps to maintain data confidence and implement data standardization practices.
• Support a data-driven culture by educating the organization on everyday uses of data, and increasingly AI, as a resource.
• Work with our Data Science / Analytics organization to help achieve product goals, including supporting model evaluation and monitoring once in production.

Qualifications

• Minimum Bachelor’s degree in a related field of study required.
• Master’s degree in a related field is highly desirable.
• Minimum of 15-20 years of technology leadership experience.
• Minimum of 5 years of experience leading teams building data platforms.
• Understanding of machine learning, with prior experience implementing end-to-end ML-powered models highly desirable; exposure to GenAI/LLM-based systems (RAG, vector search, prompt/eval pipelines) is a strong plus.
• AWS/Azure cloud experience around data integration technologies and frameworks.
• Knowledge of common ingestion patterns, ETL/ELT, and streaming architectures.
• Hands-on familiarity with modern data stack tooling (e.g., dbt, Spark/Databricks-class compute) and data observability/quality platforms.
• Proven experience working with large-scale data processing platforms and distributed computing frameworks (e.g., Spark, Snowflake, or similar), handling high-volume, high-velocity data at enterprise scale.
• Working knowledge of data governance/cataloging tools and vector database concepts.
• Knowledge of Agile development methodologies.
• Experience leading a Shared Services / Platform organization, with a client-first mentality and a collaborative, helpful attitude.
• Experience managing distributed teams across India and global time zones, with strong stakeholder management across US/UK/EU counterparts.
• Track record of managing and growing remote teams over time, including hiring, mentoring, and building out organizational capability as scope expands.
• Expert knowledge of data warehousing concepts and data schemas.
• Awareness of data privacy and security regulations relevant to legal/regulated data (GDPR, CCPA, etc.) and how they intersect with AI system design.
• Prior experience in the legal industry or legal technology is a plus, though not required.
• High level of attention to detail, quality, and effective verbal and written communication skills along with excellent follow-through.