Artificial Intelligence Software Engineer, Legal Technology

Overview

The artificial intelligence field is evolving at an unprecedented pace. In just a few years, AI technologies – especially large language models (LLMs) and multi-agent systems – have become pervasive. TransPerfect Legal is expanding our AI capabilities to address our clients' needs in eDiscovery, document review, and information-intensive workflows by pioneering innovative AI-driven solutions that tackle complex business challenges head-on.

As part of the Legal Artificial Intelligence team (Legal AI), the Artificial Intelligence Software Engineer will collaborate with AI/ML engineers, product teams, and domain experts to design and implement production-grade product solutions that leverage state-of-the-art AI to satisfy the needs of our clients.

We are a small and nimble team seeking a highly skilled individual who will help with designing, building, and support AI-powered systems that span LLM use-cases, information retrieval, agentic workflows, and traditional machine learning strategies. Projects will include classification, information detection, extraction, categorization, and AI-assisted review tools to bring meaning and actionable insights across structured and unstructured data. This role requires strong experience in modern AI development, scalable infrastructure, and a passion for continued learning and applying cutting-edge methods to real-world legal technology challenges. Experience in eDiscovery is not required but strongly valued.

Description

• Design, develop, and deploy AI/ML solutions for legal technology applications, focusing on classification, categorization, information extraction, advanced search and retrieval, and workflow automation.
• Build modular, reusable, and well-tested components that integrate AI models into scalable systems.
• Leverage LLMs, traditional ML, databases, and agent-based frameworks and orchestration to build robust, scalable solutions for both structured and unstructured data (text, images, and other media).
• Develop APIs, microservices, and pipelines to integrate AI models and solutions into client-facing platforms.
• Collaborate with project managers, domain experts, and stakeholders to identify opportunities and translate them into effective AI solutions to meet business needs.
• Ensure quality, reproducibility, monitoring, and maintainability of deployed models and solutions.
• Provide technical support and collaborate with the Support team to troubleshoot, diagnose, and resolve production issues.
• Stay current on emerging AI techniques (LLMs, agentic frameworks, retrieval-augmented generation, multimodal AI) and recommend adoption where appropriate.
• Maintain existing codebases, contributing bug fixes, optimizations, and new features.
• Proactively suggest improvements to AI development workflows, processes, pipelines, and solution design.
• Write clear technical documentation on codebases, data models, APIs, processes, and contribute to client-facing user guides to ensure clarity, maintainability, and best practices.

Job requirements

Required Skills

• Bachelor’s degree in an analytical field (or equivalent practical experience).
• 3–5 years of hands-on experience in AI/ML software engineering with end-to-end model development and deployment.
• Strong proficiency in Python and experience in related frameworks for AI / ML development and testing (PyTorch, Hugging Face, LangChain, LangFuse, MLflow, or similar), with demonstrated ability to write clean, modular, and maintainable code.
• Experience with Natural Language Processing (NLP) techniques, LLMs (Large Language Models), transformer models, vector databases (e.g., Pinecone, Chroma, Weaviate, FAISS), and agentic AI frameworks.
• Familiarity with distributed computing and scaling (e.g., Databricks, Spark, Ray, Kubernetes).
• Strong software engineering fundamentals, including APIs, RESTful web services, Docker containerization, microservices, and cloud-native architectures (AWS or Azure preferred).
• Hands-on experience with CI/CD, Git, and DevOps practices.
• Excellent problem-solving and troubleshooting skills, with the ability to independently debug complex systems.
• Strong written and verbal communication skills for technical and non-technical audiences.

Desired Skills and Experience

• Familiarity with legal eDiscovery life-cycle, document review workflows, and litigation support technologies.
• Bonus points if familiar or proficient in C# or other programming languages.
• Bonus points if familiar or experienced in Computer Vision (CV) tasks (e.g., image detection, object tracking, OCR) or Audio signals analysis (e.g., speech recognition, classification).
• Full-stack or backend software development experience.
• Experience with MLOps practices (monitoring, retraining pipelines, model versioning, model drift detection, experiment tracking).
• Cloud experience (AWS, Azure, or GCP).
• Experience leading AI projects from conceptual design to production.
• Exposure to multimodal AI (text + image / media processing).
• Contributions to open-source AI/ML frameworks, agentic orchestrations, or tools.