Jobs at Nexaminds

Design, build, test, and maintain scalable backend services, APIs, and cloud data pipelines using Java/Python on GCP. Integrate LLMs/AI services, improve AppSec, write tests, troubleshoot production issues, participate in code reviews, and collaborate with cross-functional teams.

As a Sr. Fullstack Engineer, you will design and develop scalable applications using C# and .NET for backend and React for frontend, while integrating AI technologies.

Design, build, optimize, and scale high-performance backend systems and cloud-native applications using Java, Python, and GCP. Build scalable data pipelines, microservices, and APIs; integrate LLMs/AI backends; enforce application security; conduct code reviews, testing, and documentation while collaborating with cross-functional teams.

Lead backend architecture and development of scalable, secure microservices and data pipelines using Java, Python, and GCP. Integrate LLMs/AI, enforce application security, mentor engineers, run design reviews, and drive AI-assisted tooling adoption.

Lead backend engineering for cloud-native, scalable microservices and data pipelines using Java, Python and GCP; integrate LLMs/AI, enforce application security, mentor engineers, and collaborate with product and data science teams.

Design, build, optimize, and scale backend systems and cloud-native microservices using Java, Python, and GCP. Integrate LLMs/AI backends, build data pipelines and APIs, improve cloud infrastructure availability, use GitHub Copilot for development velocity, perform code reviews, enforce AppSec practices, and remediate security vulnerabilities.

Design, develop, test, and deploy scalable backend services, APIs, and data pipelines using Java and Python on cloud platforms (GCP). Integrate and support AI/LLM services, maintain application security, write tests, troubleshoot production issues, participate in code reviews, and collaborate with cross-functional teams to deliver high-quality software.

Lead and grow an engineering team building internal developer platform capabilities and developer productivity tooling. Balance hands-on platform engineering (C#/.NET, Azure, Terraform, CI/CD, containers) with people leadership, roadmap ownership, AI-assisted developer tooling adoption, observability, and metrics-driven improvements to developer experience.

Lead data architecture for a monolith-to-distributed modernization: define domain boundaries, SQL Server→Cosmos DB migration patterns, event schema and CDC standards, ensure data ownership, reporting continuity, and partner with engineering and data lake teams to avoid extraction risks.

Design, build, and scale Azure-based data ingestion and transformation pipelines using Python and Databricks. Implement config-driven, testable ETL/ELT with PySpark and Delta Lake, enforce data quality, optimize Spark jobs, create reusable libraries and onboarding templates, and support Bronze/Silver/Gold medallion patterns and domain onboarding (Provider, Claims, Member, Eligibility). Participate in code review, documentation, and production operations.

Design, optimize, and modernize enterprise applications using Azure Cosmos DB: data modeling, partitioning, indexing, performance/RU optimization, migrations from SQL Server, implement CDC with Debezium, and design event-driven architectures.

Manage, configure, and maintain various database environments ensuring optimal performance. Responsibilities include upgrading, tuning, troubleshooting, and securing databases while supporting production deployments.

The Senior Data Engineer will develop and optimize data solutions, manage ingestion and transformation pipelines, and ensure data quality and operational reliability in AWS and Snowflake environments.

The Senior Automation & AI Engineer will design and develop automation solutions and AI-powered workflows while enhancing operational efficiency across global infrastructure, collaborating with various teams to implement these solutions.

Design, develop, and optimize scalable data solutions and data pipelines using Databricks, Python, SQL, and Azure. Collaborate across teams for data integration and quality assurance.

Lead the development, optimization, and scaling of data solutions. Design and maintain data pipelines using Databricks and collaborate with multidisciplinary teams to define requirements.

The Senior Databricks Engineer will design, build, and maintain scalable data pipelines, optimize ETL/ELT processes, and ensure data quality and governance while collaborating with teams to meet data requirements.

Responsible for designing, building, and maintaining scalable data pipelines using Databricks. Optimize ETL/ELT processes and ensure data quality, governance, and security.

Lead the development and optimization of data solutions using Databricks, build scalable data pipelines, and collaborate with teams to define data requirements.

Lead and support a ~10-person principal-level engineering team across a large modernization program. Own team health, delivery visibility, dependency management, cross-team coordination, and alignment to program standards. Balance people leadership, program coordination, and hands-on technical contribution as needed.