Design, build, and scale highly concurrent backend applications and microservices using Elixir and Phoenix. Collaborate with cross-functional teams to architect resilient, distributed systems and establish engineering best practices.
You will design, develop, and scale highly concurrent backend microservices using Elixir and Phoenix. Additionally, you will define robust distributed architectures and collaborate with international multidisciplinary teams to ensure high system availability.
You will lead the end-to-end development of generative and multimodal AI solutions, integrating them into production environments. Additionally, you will participate in model fine-tuning, testing, and ensuring system resilience through robust observability and quality controls.
Manage performance-related tickets via ServiceNow and configure solutions in QA environments for performance testing. Monitor metrics, analyze observability data, and adjust CPU and memory settings to ensure microservices operate within expected parameters.
You will act as a facilitator between business needs and infrastructure teams to design and implement scalable cloud solutions. Responsibilities include managing infrastructure requirements, participating in modernization initiatives, and overseeing automation and observability processes.
Design and implement scalable machine learning architectures on AWS, focusing on SageMaker and Amazon Neptune. Define guidelines for model development, training, deployment, and monitoring while ensuring security and operational excellence.
The Senior AWS Data Architect will guide the technical team in data architecture decisions, standards, and cloud best practices. They will also oversee the design and implementation of scalable data solutions, including Data Lake and Lakehouse architectures.
Design and develop executive, analytical, and operational dashboards in Tableau while applying data storytelling and UX principles. Provide technical and functional support to the BI team while establishing visualization standards and governance practices.
Lead and mentor a junior team in the development, training, and deployment of machine learning models on AWS. Define MLOps best practices, monitor model performance, and ensure reliability and explainability in production environments.
You will design, build, and deploy machine learning and optimization solutions to address complex business challenges within multidisciplinary product teams. Additionally, you will collaborate with engineers to deliver production-grade models while translating analytical findings into actionable recommendations for stakeholders.
Design and develop robust, scalable automations using Power Automate Cloud and Desktop. Collaborate with business and technical teams to integrate systems, manage errors, and ensure high-quality deployments.
Design, build, and maintain high-throughput data pipelines and scalable cloud data warehouse architectures for financial transactions. Collaborate with cross-functional teams to implement data quality frameworks, governance standards, and automated CI/CD workflows.
Design and maintain high-throughput batch and streaming data pipelines to process global financial transactions. Collaborate with cross-functional teams to build scalable data warehouse and lakehouse architectures while enforcing data quality and governance standards.
Lead the design, development, and delivery of end-to-end data science solutions while providing technical guidance to the team. Collaborate with business stakeholders and engineering teams to translate complex business challenges into scalable, data-driven machine learning models.
You will own the architecture, development, and automation of end-to-end machine learning solutions while bridging the gap between data science and software engineering. Responsibilities include managing the ML lifecycle, ensuring cloud cost-efficiency, and collaborating with cross-functional teams to deliver scalable production models.
You will design and implement scalable data solutions while managing cloud infrastructure and automating data operations. The role involves direct customer interaction to gather requirements and provide technical leadership for complex software initiatives.
You will be responsible for designing, developing, and operating backend solutions using Java within a complex microservices architecture. The role involves integrating messaging, asynchronous communication, and AI technologies to ensure system resilience in a fintech environment.
Lead the greenfield implementation of Microsoft Intune, Entra ID, and Microsoft Defender for Endpoint across a multi-cloud environment. Define device management policies, configure endpoint security, and facilitate knowledge transfer to internal engineering teams.
You will lead the development and optimization of efficient data pipelines between Snowflake and Google Cloud Platform. Responsibilities include implementing native orchestration, config-driven processing, and ensuring robust data governance and observability.
Lead the end-to-end migration of a native Android application to a unified React Native ecosystem for industrial plant operators. Ensure critical offline-first capabilities and resilient integration with AWS IoT and Cloud services.
