Senior Manager – Technical (Legal Technology)

Key Responsibilities

• Design and build end-to-end full-stack applications and AI-powered products to automate legal and business workflows from proof-of-concept through production deployment.
• Develop Generative Artificial Intelligence-enabled features for document understanding risk insights, decision support, and workflow automation.
• Build and orchestrate intelligent agents, agentic workflows, multi-agent systems, and multimodal AI solutions for secure enterprise processes and integrations.
• Implement Retrieval-Augmented Generation, knowledge-augmented architectures, and retrieval-augmented reasoning solutions grounded in enterprise data with governance and traceability controls.
• Architect scalable asynchronous pipelines and AI-native solutions using orchestration layers, model integrations, vector databases, APIs, security controls, observability, and deployment patterns.
• Integrate platforms and AI services with SaaS solutions, enterprise applications, and data services using APIs, webhooks, event-driven patterns, and MCP-based integrations.
• Lead solution architecture and technical design reviews, selecting and optimizing AI models and architectures based on accuracy, latency, cost, security, reasoning capability, and business requirements.
• Lead AI experimentation, rapid prototyping, model benchmarking, performance optimization, prompt engineering, retrieval optimization, and evaluation-driven improvements.
• Create technical artefacts, including architecture diagrams, data flows, integration designs, documentation, and runbooks, and enable stakeholders through training and mentorship.
• Own end-to-end architecture, production deployment, scaling, operationalization, monitoring, and continuous optimization across legal technology platforms, AI services, and integrations; mentor engineers and promote strong practices in development, documentation, and responsible Artificial Intelligence.

Essential Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or equivalent relevant experience.
• Extensive experience building enterprise-grade full-stack applications and AI-powered products in large, complex, or global organizations.
• Strong expertise in Python, including FastAPI and Django REST Framework, supported by a strong foundation in Artificial Intelligence, Machine Learning, Data Science, Statistics, Deep Learning, model evaluation, and analytical problem solving.
• Proficiency in modern front-end development with React, JavaScript or TypeScript, and styling frameworks.
• Hands-on experience with Large Language Model platforms, prompt engineering, Retrieval-Augmented Generation, retrieval-augmented reasoning, multimodal AI, and Generative Artificial Intelligence solution design.
• Experience designing AI-native solutions using orchestration layers, model integrations, vector databases, APIs, security controls, observability, and production deployment patterns.
• Strong knowledge of Azure and/or AWS cloud platforms, asynchronous processing, secure enterprise integrations, LLMOps, model monitoring, evaluation frameworks, and responsible Artificial Intelligence practices.
• Hands-on experience evaluating, selecting, and optimizing Large Language Models and AI architectures based on accuracy, latency, cost, security, reasoning capability, scalability, and business requirements.
• Experience with Azure OpenAI, AWS Bedrock, OpenAI, Anthropic, or similar platforms; AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or CrewAI; Model Context Protocol (MCP); and integration of AI services with SaaS platforms, enterprise applications, and data services.
• Proven ability to lead technical design, mentor teams, and communicate effectively with business stakeholders, with experience in conversational AI or voice intake solutions, technical diagrams and runbooks, enterprise security (SSO, OAuth, SAML, RBAC), APIs, event-driven architectures, Git, GitHub, GitLab, GitHub Copilot, AI-assisted development workflows, and relevant cloud, AI, machine learning, or solution architecture certifications.

Commitment to Diversity and Inclusion:

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.