Staff AI Engineer

Description

The company builds legal data intelligence software, with an AI-powered cloud platform used by large law firms, corporations, and government agencies for litigation, investigations, regulatory inquiries, and data breach responses.

The AI team helps users find the truth faster through AI capabilities built into the discovery process.

This Staff AI Engineer role is a domain architect and strategic accelerator. You will work across several engineering and data science teams to set the long-term direction for the machine learning platform, guide major initiatives from concept to production, and keep AI systems secure, reliable, scalable, and cost-effective.

Responsibilities

• Define and promote a multi-year technical roadmap for ML Ops that aligns platform architecture with product and research goals.
• Give technical direction and mentorship to several engineering teams and organizations.
• Design and architect training, inference, and monitoring systems that are scalable, extensible, performant, and reliable.
• Work with product, program, and data science leaders to scope and deliver cross-functional roadmaps.
• Assess new ML Ops technologies and set engineering standards and best practices.
• Push for advanced optimization methods such as sparsity, quantization, and pruning to improve performance and cost.
• Work with security teams to protect data and uphold responsible AI standards.
• Lead architecture reviews, write engineering best practices, and mentor senior and lead engineers across the company.

Requirements

• At least 8 years of professional software engineering experience.
• At least 5 years working in ML/AI or big data environments.
• At least 4 years of technical leadership across multiple teams.
• Expert-level Python, Java, or Scala for production systems.
• Deep hands-on experience with Docker, Kubernetes/Helm, and infrastructure-as-code tools such as Terraform or Pulumi.
• Proven experience building and running CI/CD pipelines for machine learning workflows with tools such as Prefect or Airflow.
• Experience deploying and running secure, monitored services on AWS, Azure, or GCP.
• A track record of mentoring senior engineers, shaping technical strategy, and driving cross-team work to completion.
• Preferred: a Master's or PhD in Computer Science, Engineering, Mathematics, or a related field.
• Preferred: recognized technical thought leadership through open-source work, conference talks, or publications.
• Preferred: experience scaling ML platforms with distributed data tools such as Spark or Kafka.
• Preferred: expertise applying advanced model optimization, including compression, pruning, and quantization, in production.

Conditions

Competitive salary, benefits, DTO, parental leave, and an equity program.

The company is committed to competitive, fair, and equitable pay.

Total compensation includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range is $205,000 to $307,000.

Final pay depends on factors such as depth of experience, skill set, qualifications, and internal pay equity. Offers at the top of the range would not be typical, leaving room for future salary growth in the role.

Skills tagged for this role: algorithms, artificial intelligence, big data, cloud computing, data science, deep learning, distributed systems, natural language, Python, software engineering.

Benefits

• Impactful work: build systems that help customers organize data, find the truth, and act on it in high-stakes legal matters.
• Scale: work on distributed, cloud-native systems that process large volumes of data.
• Current tech: build with AI, cloud platforms, and scalable architectures in legal tech.
• Ownership: own systems end to end across cloud and distributed environments.
• A team that values knowledge sharing and continuous improvement.
• An environment where diverse perspectives are valued.