AI Engineer

• Lead day-to-day delivery of complex AI engagements across strategy, product, technology, and transformation
• Connect AI initiatives to business cases, roadmaps, capabilities, operating changes, and adoption
• Help clients identify where AI can create meaningful value and determine what needs to change for solutions to succeed at scale
• Translate lessons from products and use cases into broader organizational implications
• Translate business priorities and user problems into AI opportunities
• Lead product discovery with client teams and end users
• Shape AI products and solutions from concept through prototype, build, deployment, and adoption
• Define priorities, success measures, and the optimal path to value
• Lead AI engineers, designers, and client teams across business, user, and technical needs
• Prototype and test ideas using modern AI tools, agents, workflows, and automations
• Own delivery across multiple workstreams, structure work, set priorities, and solve problems proactively
• Build trusted relationships with senior client stakeholders through workshops and challenging assumptions
• Take increasing ownership of client relationships, proposals, and commercial opportunities

Applied AI Lead

• Advise law firm stakeholders, including CFOs, billing managers, and revenue operations leads, on strategic AI value
• Prioritize work-to-cash workflows and practice areas for Intapp Celeste
• Lead deployment of Intapp Celeste AI agents, coworkers, and playbooks
• Configure deployments around billing guidelines, client terms, and revenue standards
• Translate time entry, prebill review, invoicing, collections, and revenue recognition workflows into AI-ready processes
• Identify opportunities for automation and areas requiring human oversight
• Drive adoption across billing and finance teams
• Run walkthroughs and training sessions
• Collaborate with Industry Architects and Product leaders to inform product strategy

AI Engineer, Billing & Revenue

• Design, develop, and deploy enterprise Generative AI solutions using commercial and open-source foundation models
• Build and maintain AI agents, agent orchestration frameworks, and multi-agent systems to automate complex business processes
• Develop and implement Retrieval-Augmented Generation (RAG) architectures using enterprise knowledge repositories and structured/unstructured data sources
• Design and develop custom AI tools, hooks, skills, and integrations to extend agent capabilities and improve business outcomes
• Build and maintain MCP servers and related infrastructure to securely integrate AI systems with enterprise applications and services
• Develop AI-powered applications using Python, APIs, and cloud-native services
• Monitor, optimize, and scale data workflows to improve performance and cost-efficiency
• Develop best practices for data engineering processes, documentation, and governance
• Partner with infrastructure and security teams to implement scalable, secure, and compliant AI solutions
• Collaborate with stakeholders to identify, prioritize, and deliver high-impact AI use cases
• Provide technical guidance on AI architecture, implementation patterns, and emerging industry capabilities
• Partner with business stakeholders, software engineers, architects, and data teams to translate AI opportunities into production-ready solutions

Senior AI Engineer

• Interview local offices and functional departments to map workflows, pain points, and existing AI experiments
• Identify shared, governed capabilities and infrastructure, training, or guardrails needed by teams
• Prototype agentic workflows, Claude skills, MicroApps, and retrieval features on Claude Enterprise, MCP, APIs, Snowflake, Salesforce, and Notion
• Package reusable AI capabilities for adoption across markets
• Create templates, playbooks, starter kits, and documentation for self-service AI development
• Support knowledge capture, retrieval pipelines, and early knowledge graph work for institutional memory
• Define success metrics, output quality checks, and evaluation loops
• Contribute capabilities to Endeavor's AI Registry in line with its AI Policy
• Own meaningful projects and present internship work directly to Endeavor's CEO

AI Engineer Internship, Undergraduate or Graduate

• Own end-to-end implementation of Luminary AI for each customer through prompt engineering and orchestration
• Translate firm practices into AI experiences tailored to customer workflows
• Design and configure firm-specific AI outputs, including document summaries, client memos, trust recommendations, insights, and other AI-powered workflows
• Define and own reusable prompt libraries, configuration templates, and implementation patterns
• Partner with customers to understand trust and estate planning decisions and improve AI quality, adoption, and workflow efficiency
• Partner with Product and Engineering to turn customer learnings into reusable platform capabilities
• Support sales by demonstrating AI capabilities and communicating the value of firm-specific customization
• Lead post-sale implementation and iteration, owning AI configuration, experimentation, and ongoing optimization
• Develop implementation playbooks and best practices to scale AI adoption across the customer base

• Build tools, automations, and applications supporting internal business needs across marketing, research, and workflow optimization
• Design, test, and improve language-model-based workflows for classification, summarization, extraction, generation, and search support
• Partner with Marketing, Product, Data Science, and broader business teams to translate needs into clear, scalable solutions
• Develop Python-based services, APIs, and internal tools integrating AI capabilities into daily workflows
• Evaluate and refine system performance for quality, speed, reliability, and cost
• Identify edge cases, improve system behavior, and contribute to applied AI development best practices
• Stay current with the evolving AI landscape and help evaluate tools and approaches for adoption

Junior AI Engineer

• Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design
• Design, build, and operate production-grade agentic AI systems used across multiple products
• Own and evolve agent frameworks, orchestration layers, planning, tool use, memory strategies, retrieval and grounding pipelines, LLM infrastructure, inference and model gateways, evaluation, observability, and safety tooling
• Lead technical design reviews and guide tradeoffs involving autonomy, safety, reliability, scalability, and cost
• Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production
• Evaluate emerging models, techniques, and agentic patterns and translate them into enterprise-ready improvements
• Lead people and own HR processes including performance reviews and talent development
• Recruit top technical talent
• Lead teams in iterative product development using lean principles
• Mentor senior engineers and raise the technical bar for agentic AI development
• Shape the vision and roadmap for agentic AI experiences with Product, UX, and enterprise stakeholders
• Establish architectural standards and ensure reliable, scalable agentic AI platforms across the enterprise

Director – AI Engineering

• Serve as the primary product owner and business lead for assigned enterprise AI platforms, responsible for strategy, roadmap development, release management, governance, adoption and overall platform success.
• Maintain subject matter expertise in assigned platforms, configurations, integrations, workflows and best practices.
• Evaluate, test and deploy new platform capabilities while coordinating governance, operational, training and adoption activities.
• Partner with Information Technology, Information Security, Information Governance, the Office of the General Counsel and other stakeholders on risk, security, compliance and confidentiality considerations.
• Manage strategic vendor relationships, including roadmap discussions, service reviews, issue escalation, feature requests and renewal planning.
• Coordinate with project managers, data scientists, software developers, data engineers, knowledge management lawyers and other teams to deliver scalable solutions.
• Gather user feedback, prioritize enhancements and improve platform value and user experience.
• Drive AI enablement and adoption through communications, onboarding, training, office hours, practical guidance and change-management initiatives.
• Identify high-value legal and business use cases and translate them into practical AI-enabled workflows and solutions.
• Track and analyze adoption, engagement, utilization, user satisfaction, business impact, platform value and ROI metrics.
• Prepare executive-level updates and recommendations on product performance, roadmap decisions, vendor developments, governance, adoption and investment priorities.
• Monitor generative AI, natural language processing, information retrieval and legal technology developments.
• Provide functional escalation support for complex product questions and issues.
• Handle projects on request under the direction of executive leadership.

AI Platform Manager

• Identify, scope, and drive high-impact technical and user-facing projects across the AI team's stack
• Build systems that AI models depend on, including data, training and evaluation infrastructure, perception plumbing, and product surfaces
• Ship applications and APIs that expose AI capabilities to customers
• Mentor and advise engineers and peers on technical and personal advancement
• Drive technical decisions and implementation through hands-on, technically deep work
• Own data pipelines, including teleoperation and demonstration data ingestion, labeling and curation tooling, and dataset quality metrics
• Own training and evaluation infrastructure, including training pipelines, experiment tracking, GPU orchestration, model versioning, and deployment to robots
• Own perception integration, including camera calibration, vision pipelines, and reliable integration of model outputs into the robot runtime

Senior Software Engineer, AI Team

• Develop and improve internal AI tooling, platform capabilities, and AI-enabled product functionality
• Integrate AI capabilities and APIs into existing products
• Build LLM-powered solutions using prompt engineering, context engineering, RAG, agentic workflows, and generative AI
• Create and maintain AI harnesses, evaluations, benchmarks, and testing frameworks
• Apply ML algorithms such as linear regression, logistic regression, tree-based methods, and neural networks
• Contribute to secure, scalable AI architecture, infrastructure, DevOps, hosting, and system optimization using AWS services
• Collaborate with product, data engineering, and software engineering teams to align AI initiatives with business needs
• Track emerging AI technologies and contribute to engineering best practices
• Mentor junior engineers