Engineering Specialist _ R&D Content Authoring

Job description

: **ZS** is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by **bringing together data, science, technology** and **human ingenuity** to deliver better outcomes for all. Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a **client-first mentality** to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS. : **Architecture & Engineering Specialist – ML Engineering** **ZS’s India Capability & Expertise Center (CEC)** houses more than 60% of ZS people across three offices in New Delhi, Pune and Bengaluru. Our teams work with colleagues across North America, Europe and East Asia to create and deliver real world solutions to the clients who drive our business. The CEC maintains standards of analytical, operational and technological excellence across our capability groups. Together, our collective knowledge enables each ZS team to deliver superior results to our clients. **ZS's Scaled AI**practice is part of ZS's rich and advanced AI ecosystem, in the Architecture & Engineering Expertise Center, focused on creating continuous business value for clients using a range of innovative machine learning, deep learning, and engineering capabilities. Being part of Scaled AI practice allows you to collaborate with data scientists to create state-of-the-art AI models, create and use cutting-edge ML platforms, create and deploy advanced ML pipelines and manage the complete ML lifecycle. **What** **You’ll** **Do** - Design, architect, and implement complex technical features, applying best practices across the chosen technology stack and ensuring scalability, reliability, and maintainability. - Collaborate closely with client‑facing and cross‑functional teams to understand business context, contribute to requirements gathering, and translate solution needs into actionable technical designs. - Partner with technical architects to validate design decisions, review alternatives, and jointly define implementation approaches for high‑impact components. - Write high‑quality, production‑ready code that is modular, testable, maintainable, and resilient to edge cases and failure scenarios. - Ensure delivery excellence by adhering to architecture guidelines, coding standards, and contributing actively to design and code reviews. - Develop unit tests and higher‑level automated tests to ensure coverage of both expected and edge scenarios, improving overall solution reliability. - Use engineering tools effectively — version control, code review platforms, issue tracking systems, observability/monitoring tools — to plan, organize, and deliver work. - Participate in Agile ceremonies (scrum calls, sprint planning, retrospectives) and provide structured updates, blockers, and risk signals in a timely manner. - Drive technical exploration by rapidly evaluating emerging technologies, conducting proofs‑of‑concept, and presenting insights and recommendations to the broader team. - Support the technical architect in shaping module‑level and component‑level architecture, ensuring alignment with the broader product or project blueprint. - Break down complex, multi‑step features into clear, estimable tasks, lead the estimation process, and effectively communicate rationale to internal teams and clients. - Independently lead implementation of complex or cross‑cutting features that span multiple services, components, or application layers. - Troubleshoot and systematically debug issues using logs, alerts, monitoring dashboards, and diagnostic tools to drive quick and root‑cause‑level resolution. - Perform peer code reviews, including reviewing work from senior engineers, ensuring quality, consistency, and adherence to engineering standards. - Mentor, coach, and develop technical talent within the team, providing guidance on best practices, design patterns, and coding workflows. - Author and maintain product, asset, and technical documentation—particularly for content/authoring workflows within the R&D domain—ensuring clarity, consistency, and knowledge continuity **What** **You’ll** **Bring** - 5+ years of hands‑on experience in deploying, productionizing, and scaling ML or GenAI applications in real‑world environments. - Deep expertise in ML Engineering platforms such as SageMaker, MLflow, Kubeflow, or equivalent orchestration frameworks. - Strong command of distributed data technologies: Hive, Spark, Hadoop, and messaging/streaming systems such as Kafka, RabbitMQ, or AWS Kinesis. - Ability to quickly learn new technologies, run independent POCs, and document insights in a structured, consumable format. - Strong proficiency in at least one programming language: Python, PySpark, Java, or Scala, combined with a solid foundation in data structures and algorithmic thinking. - Hands‑on experience creating metadata‑driven, reusable patterns for data ingestion, orchestration, and pipeline automation (batch + real‑time). - Experience designing and implementing solutions on distributed/cloud platforms: AWS, Azure, GCP. - Practical exposure to CI/CD pipelines, DevOps practices, and application monitoring/observability tools - Fluency in English - Client-first mentality - Intense work ethic - Collaborative spirit and problem-solving approach : **How you’ll grow:** - Cross-functional skills development & custom learning pathways - Milestone training programs aligned to career progression opportunities - Internal mobility paths that empower growth via s-curves, individual contribution and role expansions **Perks & Benef