Title: Senior Data Scientist Years of Experience : 8+ years *Location: The selected candidate is required to work onsite at our Chennai location for the initial six-month project training and execution period. After the six months , the candidate will be offered remote opportunities.* Job Description The Senior Data Scientist will lead the development and implementation of advanced analytics and AI/ML models to solve complex business problems. This role requires deep statistical expertise, hands-on model building experience, and the ability to translate raw data into strategic insights. The candidate will collaborate with business stakeholders, data engineers, and AI engineers to deploy production-grade models that drive innovation and value. Key responsibilities Lead end-to-end model lifecycle: data exploration, feature engineering, model training, validation, deployment, and monitoring Develop predictive models, recommendation systems, anomaly detection, NLP models, and generative AI applications Conduct statistical analysis and hypothesis testing for business experimentation Optimize model performance using hyperparameter tuning, ensemble methods, and explainable AI (XAI) Collaborate with data engineering teams to improve data pipelines and quality Document methodologies, build reusable ML components, and publish technical artifacts Mentor junior data scientists and contribute to CoE-wide model governance Technical Skills ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost Statistical tools: Python (NumPy, Pandas, SciPy), R, SAS NLP & LLMs: Hugging Face Transformers, GPT APIs, BERT, LangChain Model deployment: MLflow, Docker, Azure ML, AWS Sagemaker Data visualization: Power BI, Tableau, Plotly, Seaborn SQL and NoSQL (CosmosDB, MongoDB) Git, CI/CD tools, and model monitoring platforms Qualification Masters in Data Science, Statistics, Mathematics, or Computer Science Microsoft Certified: Azure Data Scientist Associate or equivalent Proven success in delivering production-ready ML models with measurable business impact Publications or patents in AI/ML will be considered a strong advantage.
Title: Senior Data Architect Years of Experience : 5-8+ years Location: Onsite ( The selected candidate is required to relocate to Kovilpatti/ Chennai, Tamil Nadu for the initial three-month project training session). Job Description: The Senior Data Architect will design, govern, and optimize the entire data ecosystem for advanced analytics and AI workloads. This role ensures data is collected, stored, processed, and made accessible in a secure, performant, and scalable manner. The candidate will drive architecture design for structured/unstructured data, build data governance frameworks, and support the evolution of modern data platforms across cloud environments. Key responsibilities Architect enterprise data platforms using Azure/AWS/GCP and modern data lake/data mesh patterns Design logical and physical data models, semantic layers, and metadata frameworks Establish data quality, lineage, governance, and security policies Guide the development of ETL/ELT pipelines using modern tools and streaming frameworks Integrate AI and analytics solutions with operational data platforms Enable self-service BI and ML pipelines through Databricks, Synapse, or Snowflake Lead architecture reviews, design sessions, and CoE reference architecture development Technical Skills Cloud Platforms: Azure Synapse, Databricks, Azure Data Lake, AWS Redshift Data Modeling: ERWin, dbt, Power Designer Storage & Processing: Delta Lake, Cosmos DB, PostgreSQL, Hadoop, Spark Integration: Azure Data Factory, Kafka, Event Grid, SSIS Metadata/Lineage: Purview, Collibra, Informatica BI Platforms: Power BI, Tableau, Looker Security & Compliance: RBAC, encryption at rest/in transit, NIST/FISMA Qualification Bachelors or Masters in Computer Science, Information Systems, or Data Engineering Microsoft Certified: Azure Data Engineer / Azure Solutions Architect Strong experience building cloud-native data architectures Demonstrated ability to create data blueprints aligned with business strategy and compliance.
Role & responsibilities Job Description: We are seeking a skilled and proactive Business and Quality Analyst with 35 years of experience to join our dynamic team. The ideal candidate will possess a strong background in analyzing business processes, gathering complex requirements, and ensuring the quality of software solutions through comprehensive testing strategies. This role requires close collaboration with cross-functional teams, effective communication with stakeholders, and a drive for process improvement and solution delivery excellence. Key Responsibilities: Elicit, analyze, and document business and functional requirements through stakeholder interviews, workshops, and data analysis. Translate business needs into clear and comprehensive Business Requirement Documents (BRD) , Functional Specification Documents (FSD) , and User Stories . Collaborate with development, design, and QA teams to ensure solutions align with business goals and technical feasibility. Define and execute detailed test strategies , including test plans , test cases , and test scripts across different test levels. Perform functional , regression , and UAT testing to ensure system stability and business compliance. Identify and track defects using project tracking tools and work with technical teams for timely resolution. Assist product owners and project managers in backlog grooming, sprint planning, and prioritization activities. Develop and maintain process flows , user manuals , and training materials for end users. Proactively identify opportunities for process optimization , risk mitigation , and quality improvement . Participate in Agile ceremonies such as daily stand-ups, sprint reviews, retrospectives, and demos. Skills & Qualifications: Strong experience in business analysis , requirement gathering , and quality assurance across SDLC phases. Excellent documentation skills with hands-on experience in preparing BRD, FSD, wireframes, and test cases. Proficient in manual testing techniques, defect life cycle management, and test reporting. Effective communicator with the ability to interact with business and technical stakeholders at all levels. Solid understanding of Agile/Scrum methodologies and experience working in Agile environments. Experience using tools such as JIRA , Azure DevOps , Confluence , or similar for project and defect tracking. Strong organizational and multitasking skills with a focus on detail and quality. Quick learner with the ability to adapt to new domains, technologies, and business processes. Preferred candidate profile
Role & responsibilities Preferred candidate profile Job Description: Job Title : AI Developer Employment Mode : Full Time Location : Remote About the Role: We are looking for an experienced AI Developer with solid expertise in designing, developing, deploying, and monitoring AI systems, specifically AI Agents. The focus of this role is to lead the development and optimization of large-scale, productiongrade AI Agent systems, ensuring their reliability, scalability, and efficiency in realtime environments. You will be responsible for the end-to-end lifecycle of AI solutions, including designing and building AI Agent pipelines, optimizing model inference, and deploying these solutions with industry-standard monitoring and observability practices. As an AI Developer with 1-3 years of experience, you will be directly involved in architecting AI Agent frameworks, integrating multiple AI models, and ensuring the overall performance of AI systems. This includes designing backend architectures to support scalable AI applications, developing robust APIs, integrating data systems, and overseeing the deployment and monitoring of solutions to meet performance, security, and operational requirements. You will also contribute to developing and optimizing agent-based systems that combine AI models, tools, and multiple data sources, while ensuring seamless integration and performance in large-scale production environments. A strong focus on AIOps and system observability will be key to the role. What We Expect You to Bring (Essentials): • Education: Bachelors or master’s degree in computer science or related field. • Experience: 2+ years of basic experience in AI, developing and deploying AI models, with an emphasis on AI Agent-based systems. • Skills: Solid experience in backend development (e.g., FastAPI, Flask, Django) with an emphasis on scalability and performance optimization. Proficiency in working with deep learning/NLP frameworks and agent frameworks (e.g., HuggingFace, Transformers, LangChain, etc.). Hands-on experience with deep learning libraries (e.g., PyTorch, TensorFlow) and common data pre-processing techniques. Expertise in deploying, monitoring, and maintaining AI systems, including the use of containerization, CI/CD pipelines, and cloudbased deployments (Azure preferred). A strong understanding of AIOps practices for monitoring and optimizing AI systems in production. Experience in handling large-scale deployments, optimizing inference latency, throughput, and system observability. We Definitely Want You If You Have: Extensive experience building and maintaining retrieval-augmented generation (RAG) pipelines and dynamic agentic systems that integrate multiple AI models. Proven track record in building and deploying scalable AI Agent systems. Familiarity with techniques and frameworks for LLM optimization, inference performance, and multi-agent collaboration. In-depth understanding of production-level deployment, monitoring, and observability frameworks for AI solutions. Strong background in backend architecture, RESTful APIs, and integration of microservices to support AI operations at scale. Experience with database technologies (SQL and NoSQL) and designing data pipelines for AI/ML applications. Knowledge of additional programming languages and frameworks (e.g., Go, Rust, JavaScript) is a plus. What You Will Be Doing: 1. Design & Development of Production-Grade AI Systems Work on the design and development of AI Agent systems and pipelines, ensuring scalability, high availability, and fault tolerance. Implement end-to-end systems using pre-trained models, optimizing inference performance and integrating agentic components to enhance system capabilities. Develop backend components to support AI models, ensuring efficient data pipelines, model inference, and real-time AI capabilities. 2. Deployment, Optimization, and AIOps Optimize AI system deployment, including model inference performance, scaling, and reducing latency, ensuring real-time AI Agent functionality. Implement and manage containerization, CI/CD, and deployment pipelines for scalable and reliable production environments. Integrate observability and monitoring tools to proactively manage AI systems in production and handle AIOps tasks, ensuring system performance, availability, and security. 3. AI Agent Pipeline and Backend Development Build, optimize, and maintain AI Agent pipelines that combine multiple models, data sources, and tools for complex AI solutions. Design and develop backend APIs, integrating databases, authentication, authorization, and security mechanisms to support AI applications. Troubleshoot, debug, and improve backend services to ensure seamless and efficient operation of AI systems. 4. Collaboration & Continuous Improvement Collaborate with cross-functional teams, including backend engineers, data scientists, product managers, and frontend developers, to deliver AI-driven solutions. Participate in architectural discussions, code reviews, and contribute to the optimization of AI models, ensuring production-grade performance. Stay updated with the latest developments in AI/ML technologies, AIOps, and AI system optimization techniques to drive continuous improvement in the AI solutions you deliver.