AirwallexRemote · US - San Francisco$130k-$200k1h ago
NovartisPosted 2w ago
Senior Manager – Technical (Legal Technology) at Novartis scores 94 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Job Description Summary
#LI-HybridLocation: Hyderabad, India
Join us at the forefront of legal innovation, where technology meets real-world impact. As a Senior Manager – Technical (Legal Technology), you will help shape how legal services are delivered by building AI-enabled platforms that transform complex workflows into seamless digital experiences. This is a unique opportunity to combine hands-on engineering with technical leadership—designing scalable solutions, driving innovation, and influencing how legal and security functions operate globally. If you are passionate about building intelligent systems, mentoring others, and turning emerging technology into meaningful business outcomes, this role offers the chance to make a visible difference.
Job Description
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.
Skills Desired
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Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you decide that one model's output is better than another's for a given task?
- Walk me through how you've used OpenAI in your day-to-day work.
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- List these exact terms on your resume: Prompt Engineering, Rag, AI Agents, AI Evaluation, and OpenAI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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