We are seeking an accomplished Principal Data Platform Architect with deep expertise in Azure Databricks Platform to lead and manage our enterprise-scale data platform initiatives and analytics projects. The ideal candidate is a proactive, technically exceptional leader who brings a strong blend of strategic thinking, hands-on technical execution, and people management. Key Responsibilities Platform Ownership & Architecture Own and evolve the architecture and operations of our Azure Fabric and Databricks platforms. Drive the design and implementation of medallion architecture (bronze, silver, gold layers) to ensure scalable and maintainable data processing frameworks. Champion and enforce data governance , security protocols , lineage , and access controls across the data estate. Data Engineering Leadership Lead the development and optimization of high-performance data pipelines and ETL/ELT processes using Spark in Databricks platform. Architect end-to-end data workflows to support real-time and batch processing needs across various business units. Maintain and enhance data catalogs , metadata management, and discoverability to ensure data democratization. BI & Analytics Enablement Collaborate with stakeholders to deliver reliable BI reports and self-service analytics tools that translate data into actionable insights. Align data delivery with business KPIs, analytics roadmaps, and operational reporting needs. Team Leadership & Collaboration Inspire and lead a team of data engineers, architects, and analysts with a strong focus on collaboration and innovation. Foster a team-first mindset , providing mentorship and clear career development paths. Collaborate cross-functionally with Product, Engineering, Security, and Business teams to deliver high-impact solutions. Communication & Influence Communicate complex technical topics to non-technical stakeholders with clarity and confidence. Proactively identify opportunities, risks, and areas for data-driven innovation. Present architectural proposals and platform evolution strategies to executive leadership. Required Qualifications 10+ years of experience in enterprise data platforms, with proven leadership roles. Expert-level knowledge of Azure Fabric and Databricks (including Spark) . Strong experience implementing data governance frameworks , RBAC policies , encryption , and compliance (e.g., GDPR, HIPAA) . Proficient in building and scaling data pipelines , Delta Lake , Lakehouse patterns , and streaming/real-time data integration . Demonstrated experience in BI/reporting solutions (Power BI, Tableau, Looker, etc.). Deep understanding of data cataloging , metadata management, and data quality practices. Skilled in collaborative leadership , people management , and mentorship . Excellent written and verbal communication skills; adept at interfacing with both technical and executive stakeholders. Preferred Certifications in Azure or Databricks (e.g., Azure Solutions Architect, Databricks Certified Data Engineer). Proven track record in driving enterprise-scale data transformation initiatives .
Cloud & Infrastructure Engineer – Azure & Microsoft Technologies (Vadodara) We are hiring a Cloud & Infrastructure Engineer with strong experience in Microsoft Azure, Intune/MDM, Terraform, and Azure governance . The role involves designing secure and scalable cloud environments, driving automation, and ensuring smooth operations across hybrid and cloud-native infrastructure. Key Responsibilities Design and manage Azure infrastructure: compute, storage, networking, and security. Automate provisioning using Terraform and other IaC tools. Manage Microsoft Intune/MDM for endpoint security, compliance, and lifecycle management. Configure and govern Azure Active Directory , RBAC, and identity policies. Build CI/CD pipelines using Azure DevOps or GitHub Actions. Monitor cloud workloads using Azure Monitor, Log Analytics, and App Insights. Implement cloud security best practices and compliance controls. Collaborate with DevOps, security, and application teams. Maintain architecture docs, standards, and operating procedures. Support disaster recovery, backup, and high availability in Azure. Required Skills 3–6 years of cloud/infrastructure experience. Azure VMs, VNets, Storage, NSGs, Load Balancers, Azure Policy. Terraform (preferred), ARM Templates, or Bicep. Intune/MDM: device enrollment, compliance, app protection. Azure AD & Conditional Access. PowerShell / Python / Azure CLI automation. Azure Monitor, Sentinel, Log Analytics. Strong networking & security fundamentals. Experience with Git, Azure DevOps, or CI/CD automation. Preferred Qualifications AZ-104, AZ-305, Terraform Associate certifications. Experience with Windows 365, Defender for Endpoint, Azure Security Center. Hybrid AD environments. AKS or containerization knowledge. Key Traits Ownership mindset Strong documentation & communication Passion for automation, security, and cloud reliability
Location: Vadodara Department: Technology / Data & AI Job Summary We are seeking a skilled and innovative AI Engineer to design, build, and deploy AI-driven solutions using cutting-edge technologies like LLMs (Large Language Models) & its integration, RAG pipelines, Agentic AI , and enterprise-grade data platforms such as Azure Fabric, Data Lakes, and Power BI. This role requires a blend of software engineering, data engineering, and applied AI/ML capabilities with a focus on production-ready solutions that create tangible business impact. Key Responsibilities Area Responsibility AI/ML Development Design, train, and fine-tune ML models including NLP, recommendation systems, predictive analytics. LLM & Generative AI Integrate and optimize LLMs (e.g., OpenAI, Azure OpenAI, Claude, Gemini) into enterprise use cases. Agentic AI Systems Build autonomous AI agents with memory, reasoning, and workflow execution capabilities. Data Lake Integration Collaborate with Data Engineers to ingest and prepare data from Data Lake/Fabric. MLOps & Deployment Package and deploy models using containers (Docker, Kubernetes) and CI/CD pipelines. Data Governance Ensure all models use compliant, secure, and auditable data pipelines. Performance Monitoring Set up model monitoring, drift detection, and continuous improvement loops. Collaboration Work cross-functionally with product, data, and engineering teams. Required Skills and Experience 3–6 years of experience in AI/ML development or applied data science. Strong experience with Python , PyTorch/TensorFlow, LongChain, HuggingFace, Scikit-learn. Experience working with LLMs , vector databases (e.g., Pinecone, Weaviate, FAISS), and embeddings. Good understanding of Azure ML , Azure Fabric , or other cloud-based AI services. Proficiency in REST APIs, JSON, and integrating AI into applications via microservices. Familiarity with tools like Fivetran , Power BI , dbt , or Data Factory is a plus. Experience with MLOps tools like MLflow, Weights & Biases, or Azure DevOps. Knowledge of data governance , privacy, responsible AI principles, AI-driven security and predictive analytics. Preferred Qualifications Degree in Computer Science, AI, Data Science, or related field. Experience in building enterprise-grade AI copilots or chatbots. Knowledge of business domains like eCommerce, Supply Chain, or Retail. Certification in Azure AI Engineer or equivalent is a plus. Soft Skills Strong problem-solving and analytical thinking. Excellent communication and documentation skills. Entrepreneurial mindset with ability to work in fast-paced environments. Ownership-driven and collaborative. Opportunities Work on high-impact AI products with real-world business applications. Exposure to enterprise architecture, data platforms, and full AI lifecycle. Be part of a team shaping the future of GenAI and Agentic AI.
Cloud & Infrastructure Engineer – Azure & Microsoft Technologies (Vadodara) We are hiring a Cloud & Infrastructure Engineer with strong experience in Microsoft Azure, Intune/MDM, Terraform, and Azure governance . The role involves designing secure and scalable cloud environments, driving automation, and ensuring smooth operations across hybrid and cloud-native infrastructure. Key Responsibilities Design and manage Azure infrastructure: compute, storage, networking, and security. Automate provisioning using Terraform and other IaC tools. Manage Microsoft Intune/MDM for endpoint security, compliance, and lifecycle management. Configure and govern Azure Active Directory , RBAC, and identity policies. Build CI/CD pipelines using Azure DevOps or GitHub Actions. Monitor cloud workloads using Azure Monitor, Log Analytics, and App Insights. Implement cloud security best practices and compliance controls. Collaborate with DevOps, security, and application teams. Maintain architecture docs, standards, and operating procedures. Support disaster recovery, backup, and high availability in Azure. Required Skills 3–6 years of cloud/infrastructure experience. Azure VMs, VNets, Storage, NSGs, Load Balancers, Azure Policy. Terraform (preferred), ARM Templates, or Bicep. Intune/MDM: device enrollment, compliance, app protection. Azure AD & Conditional Access. PowerShell / Python / Azure CLI automation. Azure Monitor, Sentinel, Log Analytics. Strong networking & security fundamentals. Experience with Git, Azure DevOps, or CI/CD automation. Preferred Qualifications AZ-104, AZ-305, Terraform Associate certifications. Experience with Windows 365, Defender for Endpoint, Azure Security Center. Hybrid AD environments. AKS or containerization knowledge. Key Traits Ownership mindset Strong documentation & communication Passion for automation, security, and cloud reliability
Location: Vadodara Department: Technology / Data & AI Job Summary We are seeking a skilled and innovative AI Engineer to design, build, and deploy AI-driven solutions using cutting-edge technologies like LLMs (Large Language Models) & its integration, RAG pipelines, Agentic AI , and enterprise-grade data platforms such as Azure Fabric, Data Lakes, and Power BI. This role requires a blend of software engineering, data engineering, and applied AI/ML capabilities with a focus on production-ready solutions that create tangible business impact. Key Responsibilities Area Responsibility AI/ML Development Design, train, and fine-tune ML models including NLP, recommendation systems, predictive analytics. LLM & Generative AI Integrate and optimize LLMs (e.g., OpenAI, Azure OpenAI, Claude, Gemini) into enterprise use cases. Agentic AI Systems Build autonomous AI agents with memory, reasoning, and workflow execution capabilities. Data Lake Integration Collaborate with Data Engineers to ingest and prepare data from Data Lake/Fabric. MLOps & Deployment Package and deploy models using containers (Docker, Kubernetes) and CI/CD pipelines. Data Governance Ensure all models use compliant, secure, and auditable data pipelines. Performance Monitoring Set up model monitoring, drift detection, and continuous improvement loops. Collaboration Work cross-functionally with product, data, and engineering teams. Required Skills and Experience 3–6 years of experience in AI/ML development or applied data science. Strong experience with Python , PyTorch/TensorFlow, LongChain, HuggingFace, Scikit-learn. Experience working with LLMs , vector databases (e.g., Pinecone, Weaviate, FAISS), and embeddings. Good understanding of Azure ML , Azure Fabric , or other cloud-based AI services. Proficiency in REST APIs, JSON, and integrating AI into applications via microservices. Familiarity with tools like Fivetran , Power BI , dbt , or Data Factory is a plus. Experience with MLOps tools like MLflow, Weights & Biases, or Azure DevOps. Knowledge of data governance , privacy, responsible AI principles, AI-driven security and predictive analytics. Preferred Qualifications Degree in Computer Science, AI, Data Science, or related field. Experience in building enterprise-grade AI copilots or chatbots. Knowledge of business domains like eCommerce, Supply Chain, or Retail. Certification in Azure AI Engineer or equivalent is a plus. Soft Skills Strong problem-solving and analytical thinking. Excellent communication and documentation skills. Entrepreneurial mindset with ability to work in fast-paced environments. Ownership-driven and collaborative. Opportunities Work on high-impact AI products with real-world business applications. Exposure to enterprise architecture, data platforms, and full AI lifecycle. Be part of a team shaping the future of GenAI and Agentic AI.
Location: Vadodara Department: Technology / Data & AI Job Summary We’re looking for AI Engineers with strong hands-on experience building and integrating LLM-powered systems. The ideal profiles includes deep Python skills and production-grade experience with agent frameworks and modern API development. Key Requirements We are looking for someone with at least 5 years of overall backend experience and min 1-2 years of AI experience. Tech stack: Python, FastAPI, Langchain. AI & LLM Integration (prompting, orchestration, model evaluation, pipeline design) Python (production-level backend + data/ML workflows) LangGraph & LangChain (agent workflows, tools, memory, graph-based orchestration) FastAPI (robust backend services, API gateways, async execution) Key Responsibilities Area Responsibility AI/ML Development Design, train, and fine-tune ML models including NLP, recommendation systems, predictive analytics. LLM & Generative AI Integrate and optimize LLMs (e.g., OpenAI, Azure OpenAI, Claude, Gemini) into enterprise use cases. Agentic AI Systems Build autonomous AI agents with memory, reasoning, and workflow execution capabilities. Data Lake Integration Collaborate with Data Engineers to ingest and prepare data from Data Lake/Fabric. MLOps & Deployment Package and deploy models using containers (Docker, Kubernetes) and CI/CD pipelines. Data Governance Ensure all models use compliant, secure, and auditable data pipelines. Performance Monitoring Set up model monitoring, drift detection, and continuous improvement loops. Collaboration Work cross-functionally with product, data, and engineering teams. Required Skills and Experience 3–6 years of experience in AI/ML development or applied data science. Strong experience with Python , PyTorch/TensorFlow, LongChain, HuggingFace, Scikit-learn. Experience working with LLMs , vector databases (e.g., Pinecone, Weaviate, FAISS), and embeddings. Good understanding of Azure ML , Azure Fabric , or other cloud-based AI services. Proficiency in REST APIs, JSON, and integrating AI into applications via microservices. Familiarity with tools like Fivetran , Power BI , dbt , or Data Factory is a plus. Experience with MLOps tools like MLflow, Weights & Biases, or Azure DevOps. Knowledge of data governance , privacy, responsible AI principles, AI-driven security and predictive analytics. Preferred Qualifications Degree in Computer Science, AI, Data Science, or related field. Experience in building enterprise-grade AI copilots or chatbots. Knowledge of business domains like eCommerce, Supply Chain, or Retail. Certification in Azure AI Engineer or equivalent is a plus. Soft Skills Strong problem-solving and analytical thinking. Excellent communication and documentation skills. Entrepreneurial mindset with ability to work in fast-paced environments. Ownership-driven and collaborative. Opportunities Work on high-impact AI products with real-world business applications. Exposure to enterprise architecture, data platforms, and full AI lifecycle. Be part of a team shaping the future of GenAI and Agentic AI.
Location: Vadodara Department: Technology / Data & AI Job Summary We're looking for AI Engineers with strong hands-on experience building and integrating LLM-powered systems. The ideal profiles includes deep Python skills and production-grade experience with agent frameworks and modern API development. Key Requirements We are looking for someone with at least 5 years of overall backend experience and min 1-2 years of AI experience. Tech stack: Python, FastAPI, Langchain. AI & LLM Integration (prompting, orchestration, model evaluation, pipeline design) Python (production-level backend + data/ML workflows) LangGraph & LangChain (agent workflows, tools, memory, graph-based orchestration) FastAPI (robust backend services, API gateways, async execution) Key Responsibilities Area Responsibility AI/ML Development Design, train, and fine-tune ML models including NLP, recommendation systems, predictive analytics. LLM & Generative AI Integrate and optimize LLMs (e.g., OpenAI, Azure OpenAI, Claude, Gemini) into enterprise use cases. Agentic AI Systems Build autonomous AI agents with memory, reasoning, and workflow execution capabilities. Data Lake Integration Collaborate with Data Engineers to ingest and prepare data from Data Lake/Fabric. MLOps & Deployment Package and deploy models using containers (Docker, Kubernetes) and CI/CD pipelines. Data Governance Ensure all models use compliant, secure, and auditable data pipelines. Performance Monitoring Set up model monitoring, drift detection, and continuous improvement loops. Collaboration Work cross-functionally with product, data, and engineering teams. Required Skills and Experience 36 years of experience in AI/ML development or applied data science. Strong experience with Python , PyTorch/TensorFlow, LongChain, HuggingFace, Scikit-learn. Experience working with LLMs , vector databases (e.g., Pinecone, Weaviate, FAISS), and embeddings. Good understanding of Azure ML , Azure Fabric , or other cloud-based AI services. Proficiency in REST APIs, JSON, and integrating AI into applications via microservices. Familiarity with tools like Fivetran , Power BI , dbt , or Data Factory is a plus. Experience with MLOps tools like MLflow, Weights & Biases, or Azure DevOps. Knowledge of data governance , privacy, responsible AI principles, AI-driven security and predictive analytics. Preferred Qualifications Degree in Computer Science, AI, Data Science, or related field. Experience in building enterprise-grade AI copilots or chatbots. Knowledge of business domains like eCommerce, Supply Chain, or Retail. Certification in Azure AI Engineer or equivalent is a plus. Soft Skills Strong problem-solving and analytical thinking. Excellent communication and documentation skills. Entrepreneurial mindset with ability to work in fast-paced environments. Ownership-driven and collaborative. Opportunities Work on high-impact AI products with real-world business applications. Exposure to enterprise architecture, data platforms, and full AI lifecycle. Be part of a team shaping the future of GenAI and Agentic AI.
Location: Vadodara Department: Data Engineering Job Summary We are seeking a versatile Data, Analytics & MLOps Engineer to join our growing AI Engineering team. The ideal candidate is an expert in designing robust data pipelines (ETL pipeline), managing data lakes (Data lake Architect), building enterprise-grade dashboards, and enabling automation and AI/ML workflows using modern DevOps and orchestration tools. You will contribute to a unified data ecosystem that supports advanced analytics, Data quality frameworks, reporting, and AI adoption at scale. Key Responsibilities Functional Area Responsibilities Data Engineering - Design, develop, and maintain scalable data pipelines for ingestion, transformation, and quality. - Manage structured and unstructured data in Data Lakes (Azure, AWS S3, GCP). ETL/ELT Orchestration - Build ELT pipelines using Fivetran , dbt , Azure Data Factory , Apache Airflow , SSIS , Talend . Automation & Workflow - Implement and maintain automation using Power Automate , Pipefy , or Salesforce Workflows . Dashboards & BI - Develop analytics dashboards using Power BI , Tableau , Looker , or QlikView with data modeling and KPI visualizations. Data Governance - Implement data access, lineage, audit trails, and classification policies using tools like Purview , Collibra , or Alation . MLOps Engineering - Operationalize ML pipelines using MLflow , Azure ML , Kubeflow , SageMaker Pipelines . - Package and deploy models via CI/CD pipelines. DevOps & CI/CD - Integrate data and ML workflows with Azure DevOps , GitHub Actions , or GitLab CI/CD . Collaboration - Partner with data scientists, product teams, and business stakeholders to deliver insight-driven solutions. Required Skills & Experience 2–8 years of experience in Data Engineering , Analytics , or MLOps roles. Strong programming skills in SQL , Python , and optionally Scala or R . Experience with Cloud platforms : Azure (Data Lake Gen2, Synapse, Fabric), AWS (Glue, S3, Redshift), GCP (BigQuery, Dataflow). Hands-on with pipeline tools: Fivetran , dbt , ADF , Apache Nifi , Kafka . Visualization expertise in Power BI , Looker , Tableau , or similar. Experience with Power Automate , Pipefy , or Salesforce Flow to automate business processes. Understanding of data warehouse concepts and dimensional modeling. Working knowledge of DataOps , MLOps , DevOps , and related best practices. Desirable Skills Experience in event-driven architectures using Apache Kafka , Event Hub , or Pub/Sub . Familiarity with GenAI pipelines , RAG architecture , and vector databases like Pinecone , Weaviate , or Qdrant . Exposure to Data Mesh , Data Fabric , or Modern Data Stack . Experience in Salesforce Data Integration , Power Platform , or Microsoft Fabric . Hands-on with PowerShell scripting or Bash for automation. Certifications Preferred Microsoft Certified: Azure Data Engineer Associate / Azure AI Engineer Associate AWS Certified Big Data or Machine Learning GCP Professional Data Engineer dbt Fundamentals / Power BI Data Analyst Associate Soft Skills Ownership mindset and ability to work in a fast-paced, ambiguous environment. Strong verbal and written communication for stakeholder alignment. Problem-solving skills with a business-outcome-driven mindset. Opportunities Drive enterprise transformation through modern data and AI platforms. Work cross-functionally across supply chain , customer insights , marketing analytics , and finance intelligence . Engage in real-world GenAI readiness , Copilot integration , and agentic AI deployments.
Location: Vadodara Department: Technology / Data & AI Job Summary We’re looking for AI Engineers with strong hands-on experience building and integrating LLM-powered systems. The ideal profiles includes deep Python skills and production-grade experience with agent frameworks and modern API development. Key Requirements We are looking for someone with at least 5 years of overall backend experience and min 1-2 years of AI experience. Tech stack: Python, FastAPI, Langchain. AI & LLM Integration (prompting, orchestration, model evaluation, pipeline design) Python (production-level backend + data/ML workflows) LangGraph & LangChain (agent workflows, tools, memory, graph-based orchestration) FastAPI (robust backend services, API gateways, async execution) Key Responsibilities Area Responsibility AI/ML Development Design, train, and fine-tune ML models including NLP, recommendation systems, predictive analytics. LLM & Generative AI Integrate and optimize LLMs (e.g., OpenAI, Azure OpenAI, Claude, Gemini) into enterprise use cases. Agentic AI Systems Build autonomous AI agents with memory, reasoning, and workflow execution capabilities. Data Lake Integration Collaborate with Data Engineers to ingest and prepare data from Data Lake/Fabric. MLOps & Deployment Package and deploy models using containers (Docker, Kubernetes) and CI/CD pipelines. Data Governance Ensure all models use compliant, secure, and auditable data pipelines. Performance Monitoring Set up model monitoring, drift detection, and continuous improvement loops. Collaboration Work cross-functionally with product, data, and engineering teams. Required Skills and Experience 3–6 years of experience in AI/ML development or applied data science. Strong experience with Python , PyTorch/TensorFlow, LongChain, HuggingFace, Scikit-learn. Experience working with LLMs , vector databases (e.g., Pinecone, Weaviate, FAISS), and embeddings. Good understanding of Azure ML , Azure Fabric , or other cloud-based AI services. Proficiency in REST APIs, JSON, and integrating AI into applications via microservices. Familiarity with tools like Fivetran , Power BI , dbt , or Data Factory is a plus. Experience with MLOps tools like MLflow, Weights & Biases, or Azure DevOps. Knowledge of data governance , privacy, responsible AI principles, AI-driven security and predictive analytics. Preferred Qualifications Degree in Computer Science, AI, Data Science, or related field. Experience in building enterprise-grade AI copilots or chatbots. Knowledge of business domains like eCommerce, Supply Chain, or Retail. Certification in Azure AI Engineer or equivalent is a plus. Soft Skills Strong problem-solving and analytical thinking. Excellent communication and documentation skills. Entrepreneurial mindset with ability to work in fast-paced environments. Ownership-driven and collaborative. Opportunities Work on high-impact AI products with real-world business applications. Exposure to enterprise architecture, data platforms, and full AI lifecycle. Be part of a team shaping the future of GenAI and Agentic AI.