What Youll 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 Youll Bring

- At least 5+ relevant hands-on experiencein deploying andproductionizing MLmodelsat 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 inDesigning, configuring, and using ML Engineering platformslikeSagemaker,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 current 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

📌 Engineering Specialist (Bengaluru)
🏢 ZS
📍 Bengaluru