Senior Android Developer
Design, develop, and maintain high-quality native Android applications using Kotlin and Android Studio. Collaborate with backend and web engineering teams to ensure reliable API integrations and a consistent user experience.
Design, develop, and maintain high-quality native Android applications using Kotlin and Android Studio. Collaborate with backend and web engineering teams to ensure reliable API integrations and a consistent user experience.
Develop and enhance Databricks pipelines while managing business-critical data and collaborating with stakeholders. Design and implement data models to support machine learning, AI, and ad-hoc access to large datasets.
Define and lead the enterprise test automation strategy while architecting scalable, Java-based frameworks across UI, API, and data layers. Drive the governed adoption of AI tools within QA workflows and mentor engineering teams to improve quality maturity.
Define and lead the enterprise test automation strategy while driving the adoption of AI tools within QA workflows. Architect scalable Java-based automation frameworks and establish quality gates within CI/CD pipelines.
Define and lead the enterprise test automation strategy while driving the responsible adoption of AI tools within QA workflows. Architect scalable Java-based automation frameworks and establish quality gates within CI/CD pipelines to ensure delivery predictability.
The Senior Data Engineer will lead the development, optimization, and scaling of production-grade ingestion and transformation pipelines. They will also establish data quality controls and partner with SRE teams to ensure operational reliability.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to engineering teams while establishing standards for performance, reliability, and data governance.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to engineering teams while establishing standards for data platform performance and reliability.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to the engineering team while establishing best practices for data platform performance and reliability.
Design, develop, and maintain scalable data pipelines and models within a Microsoft Azure and Databricks environment. Collaborate with engineering teams to implement data platform solutions while ensuring data quality and performance optimization.
Design and implement scalable data engineering solutions within the Microsoft Azure and Databricks ecosystem. Provide technical leadership and mentorship to the data engineering team while ensuring high standards for data architecture and security.
Design, develop, and maintain scalable data pipelines and models using Microsoft Azure and Databricks. Collaborate with engineering teams to integrate enterprise data sources and optimize data processing workflows for performance and reliability.
You will work directly with customers to design, build, and deploy production-grade AI solutions using LLMs and agentic technologies. Additionally, you will act as a technical bridge between customer needs and internal product teams to influence engineering roadmaps.
Design, build, and maintain high-performing cross-platform mobile applications using .NET MAUI and C#. Integrate mobile frontends with backend services via RESTful APIs and manage data persistence using SQL databases.
Contribute to the development and maintenance of an internal platform-as-a-service to improve developer workflows and deployment reliability. Collaborate with engineering teams to identify friction points and integrate AI-assisted tools to enhance productivity.
The engineer will be responsible for endpoint deployment, patch management, and OS imaging using Microsoft SCCM/MECM. They will also manage site health, troubleshoot application deployment issues, and collaborate with security teams to remediate findings.
You will lead the design, implementation, and maintenance of robust test automation frameworks and performance testing strategies. Additionally, you will collaborate with cross-functional teams to ensure high-quality, scalable software releases and mentor junior QA engineers.
Lead the design, architecture, and maintenance of enterprise and domain data models to support strategic data transformation. Facilitate cross-functional alignment between business and technical teams to establish unified data structures and governance practices.
Design, build, and maintain scalable data pipelines using Databricks while managing CI/CD workflows via Azure Pipelines. Optimize ETL/ELT processes for performance and collaborate with stakeholders to define data requirements and ensure data quality.
You will work directly with customers to design, build, and deploy production-grade AI-powered solutions using LLMs and agentic technologies. Additionally, you will act as the technical voice of the customer to influence product roadmaps and mentor other engineers.
You will work directly with customers to design, build, and deploy production-grade AI solutions using LLMs and agentic technologies. Additionally, you will act as a technical owner to translate business requirements into scalable systems while providing feedback to internal product and engineering teams.
Lead the design and architecture of scalable microservices while standardizing CI/CD frameworks and deployment patterns. Partner with cross-functional teams to ensure system performance, security, and alignment with business goals.
Translate approved AI architectures into secure, scalable, and production-ready applications using LangChain and LangGraph. Build and deploy LLM-powered assistants, RAG pipelines, and agentic workflows while ensuring operational readiness and performance.
Translate approved AI architectures into secure, scalable, and maintainable production-ready systems using LangChain and LangGraph. Build and deploy LLM-powered applications, agentic workflows, and RAG solutions while ensuring operational readiness and performance.
The engineer will translate agentic AI architectures into secure, scalable production deployments using LangChain and LangGraph. They will also embed with customer teams to implement RAG, observability, and evaluation pipelines while ensuring operational readiness.
The UX Designer will conduct user research and usability testing to create intuitive, user-centered digital experiences. They will collaborate with product and engineering teams to translate requirements into wireframes, prototypes, and high-fidelity designs.
The engineer will design, implement, and maintain the SCCM/MECM infrastructure while managing software packaging and enterprise-wide deployments. They are also responsible for performing OS imaging, patch management, and providing Tier 2/3 support for SCCM-related incidents.
Design, develop, and maintain automated test suites for REST APIs and perform advanced SQL-based database validation. Collaborate with cross-functional teams to integrate tests into CI/CD pipelines and ensure system reliability across distributed services.
The Principal Engineer will lead architectural decisions for legacy-to-modern platform transitions and provide mentorship to scrum teams. They are responsible for developing front-end and back-end functionality while ensuring the platform meets high standards for quality, scalability, and performance.
Define and lead the AI validation strategy for LLMs, RAG systems, and agent-based workflows. Build automated evaluation pipelines and implement AI guardrails to ensure production-ready, safe, and reliable AI solutions.
Design, build, and deploy scalable backend services and data pipelines using Python and Java on Google Cloud Platform. Integrate AI/LLM capabilities into applications while maintaining high security and code quality standards.
You will play a key role in designing, developing, and maintaining robust backend systems that power the company's AI-driven applications. You will collaborate with the engineering team to ensure high-quality code and scalable architecture.
Drive new business generation within enterprise-level retail and logistics companies. Build and manage a high-value sales pipeline through strategic prospecting and executive networking to meet senior-level quotas.
Design and deploy scalable APIs and production-ready agentic solutions using Go. Collaborate with stakeholders and cross-functional teams to translate business needs into technical requirements and high-quality API integrations.
Lead the validation and quality strategy for AI-powered systems, including LLMs, RAG applications, and agent-based workflows. Build automated evaluation pipelines and implement AI guardrails to ensure production-ready, safe, and accurate AI solutions.
Design and implement scalable APIs and production-ready agentic solutions using Go. Collaborate with stakeholders and cross-functional teams to translate business needs into technical requirements and high-quality backend architectures.