Jobs at Brillio

Designs advanced statistical and machine learning models for forecasting, classification, and business analysis. Performs data preparation, exploratory analysis, hypothesis testing, regression, time-series forecasting, and probabilistic modeling using Python, PySpark, R, SAS, and SPSS. Builds and deploys predictive models with TensorFlow, PyTorch, and Scikit-learn, while developing validation, monitoring, and automated ML pipelines. Collaborates with cross-functional teams to translate business needs into analytical solutions.

Leads Java full-stack engineering for AEM and React.js applications. Designs scalable components and integrations, manages AEM Cloud Manager releases and CI/CD pipelines, resolves complex production issues, performs root cause analysis, and improves application performance, security, stability, and observability. Provides L3 support, conducts code reviews, guides L2 engineers, and supports multiple applications and release cycles within SLA commitments.

Develop and enhance Adobe Experience Manager solutions, including components, templates, workflows, Sling Models, Servlets, and OSGi services. Build responsive React.js interfaces and integrate them with AEM and REST APIs. Troubleshoot defects and performance issues, support deployments and maintenance, conduct testing and debugging, and perform code reviews. The role requires Java and Spring Boot backend expertise, modern frontend development skills, and experience with microservices architecture.

Architect and develop scalable Salesforce Lightning solutions, applications, integrations, workflows, reports, and dashboards. Lead Salesforce App Builder implementations, establish development and governance best practices, troubleshoot technical issues, collaborate with cross-functional teams, and mentor developers. The role requires deep Salesforce architecture expertise, Apex and Visualforce proficiency, API and integration experience, and familiarity with deployment tools, security features, and large-scale data migration.

Develop and maintain enterprise AEM digital platforms, including reusable components, templates, workflows, integrations, and content structures. Build React-based front ends integrated with AEM services and APIs. Support content migration, performance optimization, security, accessibility, CI/CD, testing, production troubleshooting, and cloud deployments. Collaborate with architects, UX, QA, DevOps, business stakeholders, and content authors while participating in design reviews, code reviews, and mentoring.

Leads the design, development, and maintenance of scalable Java enterprise applications using Spring Boot and microservices. Architects RESTful APIs, guides Angular or React frontend development, conducts code reviews, resolves complex issues, optimizes performance, and develops unit and integration tests. Collaborates with cross-functional teams, participates in Agile ceremonies, enforces coding standards, and contributes to reliable, timely software delivery.

Develop and maintain automated and manual tests for iOS and Android applications using Python and Appium. Build regression suites, integrate tests into CI/CD pipelines, validate APIs with Postman and SoapUI, manage test cases and defects in Zephyr, and apply BDD and TDD practices. Collaborate with engineering and product teams to define test strategies, analyze results, troubleshoot failures, and improve release quality.

Lead Salesforce Spiff implementations, including incentive and commission configuration, Salesforce integrations, data flows, requirements gathering, workshops, solution design, and stakeholder discussions. Candidates must demonstrate hands-on implementation examples, technical approaches, challenges, and outcomes, and be available to start within 30–45 days as a contingent worker or FTE.

Architects scalable Salesforce Marketing Cloud and CRM solutions, leads technical design sessions, governs custom development, integrations, data migrations, coding standards, releases, and deployments. Troubleshoots complex system issues, collaborates with stakeholders and Salesforce product teams, and supports pre-sales through discovery, technical demonstrations, and proof-of-concept development.

Leads the design, development, deployment, and operation of scalable Java microservices using Spring Boot, Spring Cloud, REST APIs, Kafka, and AWS. Responsibilities include architectural decision-making, database and persistence management, enterprise integrations, CI/CD, observability, secure development, code reviews, and mentoring junior developers.

Designs and implements Salesforce Marketing Cloud and Data Cloud solutions, including personalized multichannel journeys, audience segmentation, data ingestion, identity resolution, profile unification, activation, integrations, analytics, and campaign optimization. The role collaborates with stakeholders to define customer engagement strategies while ensuring platform scalability, governance, privacy, and compliance.

Leads enterprise architecture, AWS cloud transformation, application modernization, and Agentic AI platform initiatives. Designs hybrid cloud, microservices, distributed systems, multi-tenant SaaS, APIs, event-driven architectures, CI/CD, DevSecOps, and Infrastructure-as-Code solutions. Establishes architecture governance, security, compliance, and observability practices while collaborating with executives and engineering teams. Provides technical leadership, conducts design reviews and workshops, mentors delivery teams, and guides successful execution of transformation programs.

Develop and support scalable Pega applications, including case management, workflows, UI components, integrations, background processing, and business rules. Perform troubleshooting, code reviews, performance tuning, security compliance, deployment, and production support. Collaborate with analysts, architects, QA teams, and stakeholders in Agile/Scrum environments while contributing to estimation, sprint planning, solution design, and implementation.

Leads the architecture and engineering of scalable Snowflake data platforms, including ETL pipelines, data warehouses, streaming ingestion, stored procedures, performance optimization, security, and automation. Troubleshoots platform issues, collaborates on enterprise data initiatives, and mentors junior architects and engineers. The role requires deep Snowflake, SQL, Python, data modeling, and modern data platform expertise, with preferred experience in cloud platforms, orchestration tools, governance, and real-time analytics.

Leads enterprise quality engineering across APIs, cloud services, AI workflows, integrations, security, performance, resilience, observability, and production readiness. Defines QA strategy, test plans, quality gates, automation, defect governance, compliance validation, and release criteria. Coordinates engineering, security, infrastructure, operations, architecture, and business stakeholders while ensuring complete evidence for production promotion.

Develops advanced statistical and machine learning models for forecasting, classification, prediction, and probabilistic analysis. Uses Python, PySpark, R, SAS, SPSS, and multiple ML frameworks to build, validate, deploy, and manage scalable models. Applies time-series techniques, data quality validation, feature engineering, and model interpretability. Communicates complex findings to stakeholders and translates analytical results into actionable business recommendations.

Designs and implements scalable Salesforce Service Cloud solutions for field service, case management, self-service, and digital engagement. Develops Apex, Visualforce, and Lightning applications; configures workflows, objects, permissions, reports, and dashboards; integrates Salesforce with external systems through APIs and middleware; and implements CI/CD pipelines. Troubleshoots complex issues, optimizes performance, and ensures compliance with Salesforce governor limits.

Leads quality engineering for Python full-stack applications using microservices. Designs automated testing frameworks and regression suites for web and mobile applications, integrates tests into CI/CD pipelines, validates REST and GraphQL APIs, and manages Docker and Kubernetes test environments. Collaborates with engineering, DevOps, and product teams to resolve defects, improve test reliability and performance, and promote automation and code-quality practices across iOS, Android, and web platforms.

Develops advanced statistical and machine learning models for classification, prediction, forecasting, and probabilistic analysis. Uses Python, PySpark, R, SAS, SPSS, and numerous ML frameworks to analyze data and deliver business insights. Responsibilities include model deployment, lifecycle management, data validation, feature engineering, interpretability, and stakeholder communication. The role requires expertise in hypothesis testing, regression, time series forecasting, distributed processing, and production ML tools.

Designs and maintains automated testing frameworks and regression suites for Python fullstack web, mobile, and microservices applications. Integrates tests with CI/CD pipelines, validates REST and GraphQL APIs, manages Docker and Kubernetes test environments, troubleshoots test infrastructure, and collaborates cross-functionally to resolve defects and improve release quality.