Jobs at OneMagnify

Develop and optimize machine learning, deep learning, and generative AI models for business and customer-experience applications. Build LLM and RAG solutions, prepare datasets, perform feature engineering, evaluate models, and conduct experimentation. Collaborate with Marketing, Sales, Product, and Engineering teams to translate business needs into measurable AI solutions. The role also involves dashboarding, executive reporting, cloud platforms, and MLOps practices.

Supports budgeting, forecasting, scenario planning, workforce planning, and cost optimization for the India organization and broader finance team. Maintains financial models, monitors performance metrics, evaluates strategic initiatives, and provides analysis to Finance leadership. Partners with business leaders and BI teams to improve reporting, planning efficiency, and data-driven decision-making using modern technologies and AI.

Build and lead OneMagnify’s global FP&A Reporting Center of Excellence in India. Own executive, board, lender, and management reporting; establish scalable standards, controls, and processes; oversee budgeting, forecasting, variance analysis, and cost optimization; recruit and develop FP&A talent; and drive finance transformation through automation, Adaptive Planning, AI, and modern reporting technologies.

Leads OneMagnify’s AI practice by guiding client strategy, directing generative AI architecture and delivery, and translating business needs into production-ready solutions. Manages and mentors data scientists, AI engineers, and software engineers while overseeing Databricks-based data pipelines, model deployment, MLOps, and LLM applications. Partners across analytics, strategy, engineering, creative, and operations teams, presents technical concepts to executives, and contributes to evolving the company’s AI service offerings.

Business Analyst partners with clients and delivery teams to define requirements, create Agile user stories, support solution design, analyze SQL and business data, identify root causes, and ensure quality through testing and user acceptance. The role leads workshops, validates payment and data processes, facilitates stakeholder alignment, supports client adoption, and provides consultative guidance across technology, data, UX, development, and QA initiatives.

The Business Analyst will gather and validate requirements, translate business needs into Agile user stories, support solution design, analyze complex datasets with SQL, and conduct root cause analysis. The role partners with clients, product, UX, development, data, and QA teams throughout delivery. Responsibilities also include process modeling, payment validation, test traceability, user acceptance testing, workshops, training, client presentations, and improving analysis practices.

Leads client discovery, requirements gathering, Agile user-story development, solution design, data analysis, SQL validation, root-cause analysis, and quality assurance support. Facilitates workshops, stakeholder reviews, demonstrations, training, and user acceptance testing while coordinating application, data, UX, development, and QA teams. Provides consultative guidance throughout technology and data solution delivery, with emphasis on payment validation and accurate business outcomes.

Lead engineering delivery for Chennai teams, ensuring high-quality, client-focused software through process improvement, quality metrics, capacity planning, and mentoring Engineering Managers. Own strategic roadmap, cross-functional collaboration with Product, Architecture, DevOps, and Security, and enforce documentation, standards, and technical excellence to improve velocity, code quality, and application health.

Lead and coach multiple Agile teams to deliver digital products and platforms. Facilitate ceremonies, manage releases, surface risks and dependencies, remove impediments, coordinate cross-functional stakeholders, and use Jira/Rovo and reporting tools to drive delivery transparency and continuous improvement.

Design, develop, and maintain web applications using Microsoft .NET; design databases and ETL; write code, tests, and documentation; mentor junior developers; perform code reviews, integration testing, and production support; coordinate small projects with PM, QA, and infrastructure teams.

Lead discovery and requirements definition for complex technology and data solutions. Translate business needs into testable Agile user stories, design solution artifacts, analyze large datasets with SQL, validate payments and data accuracy, partner with QA for traceability, and support client workshops, UAT, and adoption.

Optimize LLM performance and implement evaluation frameworks; build clustering models for customer and product segmentation; design and maintain data pipelines using SQL and Python DAGs.

The role involves managing ML models, deploying them in production, evaluating technologies, and implementing CI/CD processes while supporting model development and ensuring data security.

Design, build, and maintain Adobe Commerce (Magento 2) e-commerce solutions including custom modules, REST/GraphQL APIs, third-party integrations, and performant storefronts (Luma/Hyva or headless PWA). Use AI-assisted dev tools, write testable PHP, optimize caching and search (Varnish, Redis, Elasticsearch/OpenSearch), manage CI/CD pipelines, troubleshoot issues, and collaborate with product, UX, and QA while staying current on platform releases and security patches.

Design, build, and maintain scalable backend services on Optimizely using C#/.NET 8. Develop RESTful and GraphQL APIs, integrate middleware and third-party systems, use Azure and IaC (Terraform/Bicep), apply AI-assisted development tools, write automated tests, participate in code reviews and sprint planning, and troubleshoot platform integrations.

Lead development of enterprise Power BI reporting: design star-schema models, build Power Query pipelines, author DAX measures, perform reconciliations and variance analysis, integrate CRM/ERP/time-tracking/HR data, and improve data governance and reporting standards.

The role involves developing credit risk models, enhancing AI solutions, conducting statistical analyses, and collaborating with quantitative analytics teams while ensuring adherence to data privacy standards.