The firm
This role is open to Singapore (preffered) / Hong Kong
Simpson Thacher is committed to transforming how legal services are delivered. As client expectations evolve and technology reshapes the profession, we are investing in innovation as a core strategic priority.
The Associate Director of Engineering, Legal Technology will provide technical leadership within the Knowledge & Innovation (K&I) department, driving the design, development, integration and delivery of modern legal technology solutions. This role combines hands-on architectural expertise with people leadership and strategic partnership across Knowledge, IT, and external vendors.
This role will lead engineering and solution architecture efforts across both custom-built and SaaS legal technology platforms, while serving as a subject matter expert (SME) for Search, Retrieval-Augmented Generation (RAG), and related AI-enabled knowledge systems.
This role reports to the Chief Knowledge & Innovation Officer (CKIO) and is critical to scaling the Firm's Knowledge & Innovation capabilities. The Associate Director of Engineering will help transform how attorneys access knowledge, leverage AI, and deliver value to clients—while ensuring solutions are robust, secure, and aligned with the Firm's long-term strategy
Responsibilities/Duties
Engineering & Architecture Leadership
- Lead engineering strategy and solution architecture for Knowledge & Innovation initiatives, ensuring scalability, security, and alignment with Firmwide technology standards.
- Design and oversee integrations across SaaS platforms, internal systems, data sources, and AI / LLM services used in legal workflows.
- Act as technical authority for evaluating, implementing, integrating and extending legal tech solutions (e.g., knowledge management, document intelligence, research, drafting, and workflow tools).
- Search, RAG, and AI Enablement (SME)
- Serve as a key subject matter expert for enterprise search, semantic search, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
- Provide input to document and data storage and organization approaches, to enable the most responsive and performant retrieval approaches
- Partner with Data Science, Practice Solutions & the Firm's Legal Practices to design AI-powered solutions that systematically surface Firm knowledge, precedents, and insights in a secure and auditable manner.
- Help establish best practices for data ingestion, indexing, retrieval, grounding, and evaluation of AI-driven search and generative systems.
- Conduct independent research to stay current on emerging retrieval techniques and their applicability to the Firm
Team Leadership & Delivery
- Lead and mentor a small, high-performing engineering team supporting both custom development and SaaS configuration, integration and extension (focused on lawyer tools).
- Work with IT to set technical direction, establish protocols, review designs and code, and ensure consistent engineering quality and documentation.
- Manage delivery across multiple initiatives, balancing rapid experimentation with production-grade reliability.
Vendor & SaaS Enablement
- Act as technical lead for vendor engagements, including solution viability, design reviews, integrations, and roadmap alignment.
- Oversee customization, configuration, and extension of SaaS legal tech platforms through APIs, middleware, and automation.
- Evaluate emerging legal technology and AI vendors in partnership with Practice Solutions, Data Science and Knowledge Management teams.
Required Skills
- 10+ years of experience in software engineering, solution architecture, or platform engineering, with at least 5 years in a technical leadership role.
- Demonstrated experience designing and implementing search platforms, semantic search, or RAG-based systems.
- Strong experience with cloud-based architectures, APIs, and modern development frameworks.
- Proven ability to lead small engineering teams and deliver complex, cross-functional initiatives.
Preferred Skills
- Experience in legal technology, professional services, or other highly regulated environments.
- Experience with document-specific segmentation and storage approaches.
- Familiarity with LLM-integrated search platforms, vector databases, term frequency approaches, structural and hierarchical indexing, knowledge graphs, and corresponding AI governance considerations.
- Familiarity with document classification, text classification and named entity recognition techniques.
- Experience integrating and extending enterprise SaaS platforms.
- Exposure to knowledge management systems, document management systems (DMS), or legal research tools
Required Education
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Details
Key Competencies
- Technical leadership and architectural judgment
- Strong communication skills with both technical and non-technical stakeholders
- Pragmatic, business-oriented approach to engineering and innovation
- Ability to balance experimentation with enterprise-grade reliability and security
- Curiosity and continuous learning mindset, particularly in AI and legal tech
