About Us At Bank of America we are guided by a common purpose to help make financial lives better through the power of every connection Responsible Growth is how we run our company and how we deliver for our clients teammates communities and shareholders every day One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world We re devoted to being a diverse and inclusive workplace for everyone We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical emotional and financial well-being Bank of America believes both in the importance of working together and offering flexibility to our employees We use a multi-faceted approach for flexibility depending on the various roles in our organization Working at Bank of America will give you a great career with opportunities to learn grow and make an impact along with the power to make a difference Join us Global Business Services Global Business Services delivers Technology and Operations capabilities to Lines of Business and Staff Support Functions of Bank of America through a centrally managed globally integrated delivery model and globally resilient operations Global Business Services is recognized for flawless execution sound risk management operational resiliency operational excellence and innovation In India we are present in five locations and operate as BA Continuum India Private Limited BACI a non-banking subsidiary of Bank of America Corporation and the operating company for India operations of Global Business Services Process Overview The Data Analytics Strategy platform and decision tool team is responsible for Data strategy for entire CSWT and development of platforms which supports the Data Strategy Data Science platform Graph Data Platform Enterprise Events Hub are key platforms of Data Platform initiative We re seeking a highly skilled AI ML Platform Engineer to architect and build a modern scalable and secure Data Science and Analytical Platform This pivotal role will drive end-to-end E2E model lifecycle management establish robust platform governance and create the foundational infrastructure for developing deploying and managing Machine Learning models across both on-premise and hybrid cloud environments Responsibilities Lead the architecture and design for building scalable resilient and secure distributed applications ensuring compliance with organizational technology guidelines security standards and industry best practices like 12-factor principles and well-architected framework guidelines Actively contribute to hands-on coding building core components APIs and microservices while ensuring high code quality maintainability and performance Ensure adherence to engineering excellence standards and compliance with key organizational metrics such as code quality test coverage and defect rates Integrate secure development practices including data encryption secure authentication and vulnerability management into the application lifecycle Work on adopting and aligning development practices with CI CD best practices to enable efficient build and deployment of the application on the target platforms like VMs and or Container orchestration platforms like Kubernetes OpenShift etc Collaborate with stakeholders to align technical solutions business requirements driving informed decision-making and effective communication across teams Mentor team members advocate best practices and promote a culture if continuous improvement and innovation in engineering processes Develop productive utilities automation frameworks data science platforms that can be utilized across multiple Data Science teams Propose Build variety of efficient Data pipelines to support the ML Model building deployment Propose Build automated deployment pipelines to enable self-help continuous deployment process for the Data Science teams Analyze understand execute and resolve the issues in user scripts model code Perform release and upgrade activities as required Well versed in the open-source technology and aware of emerging 3rd party technology tools in AI-ML space Ability to fire fight propose fix guide the team towards day-to-day issues in production Ability to train partner Data Science teams on frameworks and platform Flexible with time and shift to support the project requirements It doesn t include any night shift This position doesn t include any L1 or L2 first line of support responsibility Requirements Education Graduation Post Graduation BE B Tech MCA MTech Certifications If Any FullStack Bigdata Experience Range 11 Years Foundational Skills Microservices API Development Strong proficiency in Python building performant microservices and REST APIs using frameworks like FastAPI and Flask API Gateway Security Hands-on experience with API gateway technologies like Apache APISIX or similar e g Kong Envoy for managing and securing API traffic including JWT OAuth2 based authentication Observability Monitoring Proven ability to monitor log and troubleshoot model APIs and platform services using tools such as Prometheus Grafana or the ELK EFK stack Policy Governance Proficiency with Open Policy Agent OPA or similar policy-as-code frameworks for implementing and enforcing governance policies MLOps Expertise Solid understanding of MLOps capabilities including ML model versioning registry and lifecycle automation using tools like MLflow Kubeflow or custom metadata solutions Multi-Tenancy Experience designing and implementing multi-tenant architectures for shared model and data infrastructure Containerization Orchestration Strong knowledge of Docker and Kubernetes for containerization and orchestration CI CD GitOps Familiarity with CI CD tools and GitOps practices for automated deployments and infrastructure management Hybrid Cloud Deployments Understanding of hybrid deployment strategies across on-premise virtual machines and public cloud platforms AWS Azure GCP Data science workbench understanding Basic understanding of the requirements for data science workloads Distributed training frameworks like Apache Spark Dash and IDE s like Jupyter notebooks abd VScode Desired Skills Security Architecture Understanding of zero-trust security architecture and secure API design patterns Model Serving Frameworks Knowledge of specialized model serving frameworks like Triton Inference Server Vector Databases Familiarity with Vector databases e g Redis Qdrant and embedding stores Data Lineage Metadata Exposure to data lineage and metadata management using tools like DataHub or OpenMetadata Codes solutions and unit test to deliver a requirement story per the defined acceptance criteria and compliance requirements Utilizes multiple architectural components across data application business in design and development of client requirements Performs Continuous Integration and Continuous Development CI-CD activities Contributes to story refinement and definition of requirements Participates in estimating work necessary to realize a story requirement through the delivery lifecycle Extensive hands on supporting platforms to allow modelling and analysts go through the complete model lifecycle management data munging model develop train governance deployment Experience with model deployment scoring and monitoring for batch and real-time on various different technologies and platforms Experience in Hadoop cluster and integration includes ETL streaming and API styles of integration Experience in automation for deployment using Ansible Playbooks scripting Experience with developing and building RESTful API services in an efficient and scalable manner Design and build and deploy streaming and batch data pipelines capable of processing and storing large datasets quickly and reliably using Kafka Spark and YARN for large volumes of data TBs Experience designing and building full stack solutions utilizing distributed computing or multi-node architecture for large datasets terabytes to petabyte scale Experience with processing and deployment technologies such YARN Kubernetes Containers and Serverless Compute for model development and training Hands on experience working in a Cloud Platform AWS Azure GCP to support the Data Science Effective communication Strong stakeholder engagement skills Proven ability in leading and mentoring a team of software engineers in a dynamic environment Work Timings 11 30 AM to 8 30 PM IST Job Location Chennai GIFT Mumbai

📌 Data Engineer Iii - Gbs Ind (Chennai)
🏢 Bank Of America
📍 Chennai