Director, Data Science

Majesco isn’t just riding the AI wave – we’re leading it for the P&C and L&AH insurance industry. Born in the cloud and built with an AI-native vision, we’ve reimagined the insurance core as a platform that lets insurers move faster, see farther, and operate smarter. As leaders in intelligent SaaS solutions, we’ve embedded AI and Agentic AI throughout our robust product portfolio of core, underwriting, loss control, distribution, and digital solutions so our customers can reimagine their business with real-time business insights, optimized operations, and enhanced business outcomes. Everything we build is designed to strip away complexity and let our clients focus on what matters: delivering exceptional products, experiences, and outcomes.

In a world where change is constant, our native-cloud SaaS platform empowers insurers the agility to adapt to market and risk shifts quickly, reshape their operational cost structure, accelerate innovation readiness, and rethink how insurance can be done with the intelligence to stay ahead. With 1000+ implementations, we are the AI insurance leader that over 350 insurers, reinsurers, MGAs rely on to rethink how insurance can be done in today’s modern era of insurance. Break free from the past and build the future of insurance.

Director of Engineering, AI and Data Science

About the role

The Director of Engineering, AI and Data Science will lead a high-impact team of 4 data scientists and ML engineers delivering production-grade AI for Majesco insurance platforms. This leader is a hands-on practitioner and the in-house expert on the deeper, more complex aspects of LLMs, responsible for moving rapidly from idea to shipped capability while upholding high standards for code quality, reliability, and security. Reports to the VP, Product Management.

Location

US-based, Eastern Time core hours. Occasional off-hours meetings to collaborate across Majesco’s global teams and customer base.

What you’ll do

• Lead, mentor, and grow a small, senior team of 4 to deliver AI features and services with measurable business outcomes.
• Own end-to-end solution delivery for LLM use cases: problem framing, prompt engineering, fine-tuning, evaluation, safety/guardrails, deployment, monitoring, and continuous improvement.
• Serve as the organization’s hands-on expert in Microsoft Azure AI—especially Azure OpenAI—and guide pragmatic choices across Azure services (e.g., Azure ML, Cognitive Search, AKS, Azure DevOps, Cosmos DB, Key Vault) to ship scalable, secure solutions.
• Drive LLM application patterns including retrieval-augmented generation (RAG), tools/functions, and agentic frameworks for workflow automation and reasoning.
• Maintain a high bar for engineering execution: Python 3, PyTorch, CUDA, Git, test automation, CI/CD, observability, and robust rollback/recovery practices.
• Run iterative experimentation at pace: compare model architectures, prompts, tuning strategies, and evaluation methodologies; champion offline and online evaluation you can trust.
• Partner closely with Product, Design, and GTM to translate insurance business needs into clear ML problem statements and delightful user experiences.
• Architect and evolve services for uptime, latency, and reliability on GNU/Linux and Windows, with strong observability and incident response across environments.
• Champion security, privacy, and data governance in everything the team ships (PII handling, access controls, secrets management, auditability).
• Co-own cloud cost stewardship: instrument cost drivers, benchmark alternatives, and implement right-sized, cost-aware architectures.
• Guide team-run infrastructure with DevOps best practices; encourage Infrastructure as Code using Terraform and/or Azure Bicep; strengthen release hygiene and environment parity.
• Communicate crisply with stakeholders: roadmaps, KPIs, risk/mitigation, and customer outcomes; be ready to pivot priorities when new opportunities emerge.
• Stay current on advances in NLU, computer vision, information retrieval, RAG, and agentic frameworks; bring informed recommendations to a curious, technical leadership team.

What you’ll bring (minimum qualifications)

• Bachelor’s degree in a technical field (e.g., Computer Science, Engineering, Mathematics) or equivalent practical experience.
• 8+ years in software product development with proven team leadership responsibilities.
• Demonstrated success implementing LLMs in production, including prompt engineering, fine-tuning, evaluation, and safety/guardrails.
• Deep, hands-on expertise with Microsoft Azure for AI, with strong experience in Azure OpenAI.
• Strong engineering fundamentals: Python 3, PyTorch, CUDA, Git, software architec