ZS Associates—Business Technology Solutions Consultant - AI Engineering

Job description

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. 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 and implement technical features leveraging best practices for technology stack being used - Collaborate with client-facing teams to understand solution context and contribute to technical requirement gathering and analysis - Work with technical architects on the team to validate design and implementation approach - Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors - Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews - Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths - Uses bug tracking, code review, version control, and other tools to organize and deliver work - Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies - Consistently contribute in researching & evaluating the latest technologies through rapid learning, conducting proofs-of-concept and creating prototype solutions - Support the project architect in designing modules/component of the overall project/product architecture - Breaks down large features into estimable tasks lead estimation and can defend them with clients - Implement complex features with limited guidance from the engineering lead. For example service or application-wide change - Systematically debug code issues/bugs using stack traces, logs, monitoring tools, and other resources - Performs code/script reviews of senior engineers in the team - Mentor and groom technical talent within the team What You’ll Bring - At least 5-7 relevant hands-on experience in deploying and productionizing ML models at scale  - Experience in scaling GenAI or similar applications to accommodate a high number of users, large data size, and reduce response time. - Strong knowledge in developing RAG-based pipelines using frameworks like LangChain & LlamaIndex - Experience in creating GenAI applications such as answering engines, extraction components, and content authoring. - Expertise in Designing, configuring, and using ML Engineering platforms like Sagemaker, MLFlow, Kubeflow, or other platforms  - Big data - Hive, Spark, Hadoop, queuing system like Apache Kafka/Rabbit MQ/AWS Kinesis - Ability to quickly adapt to new technology and be innovative in creating solutions - Ability to independently run POCs on new technologies and document findings to share - Strong in at least one of the Programming languages - PySpark, Python or Java, Scala, etc. and Programming basics - Data Structures - Hands-on experience in building metadata-driven, reusable design patterns for data pipeline, orchestration, ingestion patterns (batch, real-time) - Experience in designing and implementation of solution on distributed computing and cloud services platform (but not limited to) - AWS, Azure, GCP - Hands-on experience building CI/CD pipelines and awareness of practices for application monitoring - 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 & Benefits: At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well‑being, financial future, time away, and professional development. With robust skills‑building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you’ll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in India, visit ZS India office locations | Where we work | ZS. Hybrid working model: We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Travel: Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures. Considering applying? At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systems—the ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are integral to your success here. We are committed to building a team that reflects a broad variety of backgrounds, perspectives, and experiences. Learn more about our inclusion and belonging efforts and the networks ZS supports to assist our ZSers in cultivating community spaces and obtaining the resources they need to thrive. If you’re eager to grow, contribute, and bring your unique self to our work, we encourage you to apply. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To complete your application: Candidates must possess or be able to obtain work authorization for their intended country of employment. An on-line application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE. Find Out More At: www.zs.com Responsibilities: 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 and implement technical features leveraging best practices for technology stack being used - Collaborate with client-facing teams to understand solution context and contribute to technical requirement gathering and analysis - Work with technical architects on the team to validate design and implementation approach - Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors - Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews - Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths - Uses bug tracking, code review, version control, and other tools to organize and deliver work - Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies - Consistently contribute in researching & evaluating the latest technologies through rapid learning, conducting proofs-of-concept and creating prototype solutions - Support the project architect in designing modules/component of the overall project/product architecture - Breaks down large features into estimable tasks lead estimation and can defend them with clients - Implement complex features with limited guidance from the engineering lead. For example service or application-wide change - Systematically debug code issues/bugs using stack traces, logs, monitoring tools, and other resources - Performs code/script reviews of senior engineers in the team - Mentor and groom technical talent within the team What You’ll Bring - At least 5-7 relevant hands-on experience in deploying and productionizing ML models at scale  - Experience in scaling GenAI or similar applications to accommodate a high number of users, large data size, and reduce response time. - Strong knowledge in developing RAG-based pipelines using frameworks like LangChain & LlamaIndex - Experience in creating GenAI applications such as answering engines, extraction components, and content authoring. - Expertise in Designing, configuring, and using ML Engineering platforms like Sagemaker, MLFlow, Kubeflow, or other platforms  - Big data - Hive, Spark, Hadoop, queuing system like Apache Kafka/Rabbit MQ/AWS Kinesis - Ability to quickly adapt to new technology and be innovative in creating solutions - Ability to independently run POCs on new technologies and document findings to share - Strong in at least one of the Programming languages - PySpark, Python or Java, Scala, etc. and Programming basics - Data Structures - Hands-on experience in building metadata-driven, reusable design patterns for data pipeline, orchestration, ingestion patterns (batch, real-time) - Experience in designing and implementation of solution on distributed computing and cloud services platform (but not limited to) - AWS, Azure, GCP - Hands-on experience building CI/CD pipelines and awareness of practices for application monitoring - Fluency in English - Client-first mentality - Intense work ethic - Collaborative spirit and problem-solving approach