Jobs at Nexaminds

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 maintain scalable backend services and data pipelines primarily in Python while supporting and enhancing Java services on GCP. Integrate LLM/AI capabilities, enforce AppSec practices, modernize cloud infrastructure, conduct code reviews, and collaborate with product, data, and infrastructure teams to deliver reliable, tested backend solutions.

Design, develop, and maintain scalable backend systems using PHP and modern frameworks. Own database integrations (SQL/NoSQL), automated testing, CI/CD, and collaborate in Agile teams. Provide technical leadership, mentor peers, and ensure best practices in architecture and code quality.

Work on customer-facing AI projects building AI-powered applications, intelligent agents, and automation workflows. Experiment with LLMs and cloud-native technologies, contribute reusable components to the platform, support design/testing/deployment, participate in code reviews, document solutions, and research emerging AI tools and best practices.

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.

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 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.

Design, build, deploy, and support scalable Go-based APIs and production agentic AI solutions. Collaborate with product, data science, and infrastructure teams to translate requirements, implement microservices on cloud (Azure/GCP), ensure reliability (SLOs, CI/CD), produce API documentation and partner enablement assets, and optimize cost, security, and operational readiness.

Design, develop, and maintain scalable full‑stack web applications using React/Next.js and Java/Spring Boot. Implement backend services, frontend features, test automation, monitoring, and support high‑traffic production systems. Influence product roadmap, translate business needs into technical solutions, and mentor teammates.

Lead complex, high-value sales cycles into enterprise retail and logistics accounts. Build and manage pipeline through prospecting and executive networking, close multi-stakeholder deals, meet senior-level quotas, and independently own a territory or vertical.

Design, build, deploy, and support scalable backend APIs and agentic AI solutions using Go. Architect microservices and cloud infrastructure (Azure/GCP), integrate data platforms, create API docs and partner enablement assets, and ensure operational readiness with CI/CD, SLOs, and security-by-design.

Lead AI validation strategy for LLMs, RAG, and agent systems. Build automated CI/CD-integrated evaluation pipelines, design semantic and prompt regression tests, implement guardrails and confidence scoring, monitor production AI quality, and define metrics/KPIs in partnership with engineering and governance teams.

Design and build scalable Node.js backend services and AI-powered integrations. Implement LLM API integrations, RAG, vector DBs, AI orchestration, message-queue-driven architectures, CI/CD pipelines, and collaborate on architecture, testing, and reliability.

Lead product for a retail sales data platform: define requirements, prioritize backlog, collaborate with stakeholders and engineering, support legacy-to-modernization migrations, use SQL for analysis and validation, monitor product performance, and drive delivery in an Agile environment.

Serve as the quality SME on a Scrum team to validate retail sales data across systems. Design, build, and maintain automated tests, write SQL queries to verify transformations, test ETL/data pipelines and APIs, investigate defects, and collaborate with developers and data engineers to ensure data accuracy, completeness, and reliability throughout the development lifecycle.

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.

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, 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.