Director of Engineering, AI and 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

Location: United States (Remote, Eastern Time core hours, Occasional off-hours collaboration with global teams)

About the Role

The Director of Engineering, AI and Data Science will lead a high-impact team of data scientists and ML engineers delivering production-grade AI and machine learning solutions for Majesco’s insurance platforms.

This leader is a hands-on engineering practitioner and in-house expert on large language models (LLMs), responsible for moving rapidly from concept to deployed capability while upholding the highest standards for code quality, scalability, reliability, and security.

You’ll shape how Majesco applies Generative AI, retrieval-augmented generation (RAG), and Azure OpenAI across underwriting, claims, and analytics workflows—transforming how insurers operate. Reports to: VP, Product Management

What You’ll Do

• Lead, mentor, and expand a high-performing AI and ML engineering team delivering measurable business value.
• Own end-to-end LLM solution delivery—from problem framing and data preparation to fine-tuning, safety guardrails, evaluation, deployment, and monitoring.
• Serve as Majesco’s subject-matter expert in Microsoft Azure AI, guiding pragmatic choices across Azure OpenAI, Azure ML, Cognitive Search, AKS, Cosmos DB, and Key Vault.
• Architect and operationalize RAG pipelines, AI agents, and workflow automation frameworks to enhance customer experience and operational efficiency.
• Uphold strong engineering excellence—Python 3, PyTorch, CUDA, CI/CD, observability, testing, and secure release management.
• Drive fast-paced experimentation to evaluate prompts, models, and architectures; champion trustworthy offline and online evaluation.
• Partner cross-functionally with Product, Design, and GTM teams to convert complex insurance problems into intuitive AI-driven solutions.
• Ensure system reliability, scalability, and uptime across environments using DevOps best practices and Infrastructure as Code (Terraform or Azure Bicep).
• Promote AI security, compliance, and data governance across all deployments—covering PII, access control, and auditability.
• Optimize cloud costs through data-driven architecture decisions and continuous performance tuning.
• Communicate clear roadmaps, KPIs, and risk assessments to stakeholders; pivot effectively as new priorities arise.
• Stay at the forefront of LLM, NLU, computer vision, and agentic AI innovations, applying emerging techniques with pragmatic rigor.

What You’ll Bring

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related technical field (advanced degree preferred).
• 8+ years of experience in software engineering or applied machine learning, including leadership of senior technical teams.
• Proven success deploying LLMs and generative AI applications in production (prompt engineering, fine-tuning, safety/guardrails).
• Deep, hands-on experience with Microsoft Azure for AI, especially Azure OpenAI and related services.
• Strong software engineering fundamentals: Python, PyTorch, CUDA, Git, CI/CD, test automation, and secur