Senior Manager, Software Engineering - AI

Role overview A legal technology company is hiring a Senior Manager of Engineering to lead its AI Search team, which owns the embedding models and indexing pipelines behind semantic search across the platform. The position reports to the Director of Engineering for AI and partners with Product, Architecture, and Data Science leaders to deliver enterprise-grade search capabilities used by legal professionals. It blends platform strategy, people leadership, and delivery execution across multiple verticals.

Responsibilities - Set and execute the long-term engineering strategy for AI Search, emphasizing embedding quality, indexing reliability, and semantic relevance across verticals. - Translate customer and product needs into scalable, production-ready search capabilities in partnership with Product, Architecture, and vertical engineering leads. - Maintain a roadmap that balances platform investment with cross-team commitments. - Oversee delivery across multiple teams to keep releases on time and high quality. - Manage, mentor, and grow engineers and technical staff, including hiring, performance management, and career development. - Foster collaboration and continuous improvement while balancing innovation with operational rigor.

Requirements - Significant engineering leadership experience managing managers or senior ICs, ideally in search, AI, or platform teams. - Hands-on background with machine learning lifecycle management, particularly embedding or NLP models. - Experience building or operating large-scale data pipelines, including indexing, transformation, or ETL. - Deep familiarity with modern engineering practices such as CI/CD, microservices, and scalable architectures. - Strong stakeholder management and executive communication skills, including navigating cross-team dependencies. - Ability to synthesize complex technical detail for leadership and cross-functional audiences.

Nice to have - Hands-on experience with semantic search or dense vector retrieval, including embedding selection or hybrid search. - Experience with Elasticsearch or OpenSearch. - Familiarity with retrieval augmented generation (RAG) pipelines and downstream LLM applications. - Background in information retrieval or natural language processing. - Experience adapting a shared platform capability across multiple product verticals or customer segments. - A track record of building engaged, high-performing engineering teams.

Benefits and work setup - Cash compensation range of $190,000–$215,000, with some roles eligible for overtime. - Approximately 90% of healthcare premiums covered, plus an HSA company contribution. - 401(k) with a 4% match and immediate vesting. - Flexible paid time off, typically three to four weeks per year, plus ten paid holidays. - Monthly contributions toward life activities and wellness, and access to LinkedIn Learning with dedicated exploration time.