Jobs at Nexaminds

Design, develop, deploy, and maintain MuleSoft APIs and integrations using Mule 4, Anypoint Platform, and API-led connectivity. Build DataWeave transformations, RAML/OpenAPI specifications, MUnit tests, security policies, monitoring, and error handling. Manage deployments across CloudHub, Runtime Fabric, and on-premises environments; contribute to CI/CD pipelines and code reviews. Collaborate with cross-functional Agile teams and mentor junior engineers.

Design, develop, and maintain enterprise applications using .NET, C#, Angular, SQL Server, Azure, microservices, Docker, and Kubernetes. Provide technical leadership, mentor developers, support Agile and Scrum activities, resolve complex production issues, contribute to architecture and distributed messaging decisions, and coordinate with product, business, and external teams to deliver reliable, scalable software.

Design, develop, test, and deploy production AI and machine learning applications, including LLM features, RAG pipelines, agent workflows, predictive models, and automation. Build data pipelines, integrate AI solutions with enterprise platforms, monitor production performance, and improve deployed systems. Collaborate with product, data, business, and engineering teams while documenting architectures and following responsible AI practices.

Design, operate, and improve AWS cloud infrastructure for large-scale customer-facing services. Build infrastructure automation, AI-driven operational workflows, patching and update pipelines, observability tooling, and incident-response processes. Troubleshoot production systems across Kubernetes, databases, regions, and cloud services while improving reliability and reducing on-call workload. Collaborate with distributed engineering teams on production readiness, postmortems, CI/CD, SLAs, and continuous improvement.

Build and maintain scalable data pipelines, ETL/ELT processes, data models, metric definitions, and data infrastructure. Develop production solutions with Python, SQL, Spark, dbt, Fivetran, Airflow, Databricks, Azure, and cloud storage. Collaborate with data scientists, engineers, analysts, and stakeholders to deliver reliable, accessible data and self-service tools. Troubleshoot pipeline issues, improve data quality and scalability, and use AI-assisted development tools to accelerate engineering work.

Lead an internal developer platform and productivity engineering team in a player-coach role. Manage distributed teams, sprint delivery, performance, hiring, and stakeholder communication while contributing to architecture, technical decisions, coding, and platform delivery. Drive cloud infrastructure, CI/CD, developer tooling, agile execution, and adoption of AI-assisted development tools. Partner with product, DevOps, and QA teams to manage capacity, dependencies, risks, and roadmap execution.

Lead hands-on modernization of a live Vue and PHP application. Build responsive, accessible, and performant interfaces; improve component architecture, CSS, state management, and front-end quality; integrate RESTful APIs; review code; resolve UI performance issues; and collaborate with product and UX teams. Use AI-assisted development tools to accelerate delivery and ramp quickly on legacy codebases.

Lead hands-on modernization of a live Vue and PHP application by converting legacy jQuery pages into accessible, responsive Vue components. Establish front-end architecture, component standards, CSS and state-management patterns, performance practices, testing, and code-review quality. Collaborate with product and UX teams, integrate RESTful APIs, resolve UI bottlenecks, and use AI-assisted development tools to accelerate delivery and navigate legacy code.

Build and enhance data engineering frameworks, scalable data solutions, centralized ETL logic, metric definitions, and concise data models. Develop self-service data tools supporting data science, internal applications, and organizational decision-making. Collaborate with cross-functional stakeholders, use AI coding agents such as Claude Code or Codex, and write production-level Python and SQL.

Leads end-to-end technology projects in healthcare, coordinating Engineering, Product, QA, Infrastructure, and business teams. Manages project plans, timelines, budgets, risks, dependencies, resources, stakeholder communications, Agile ceremonies, governance, compliance, and delivery quality. Drives issue resolution, executive reporting, and continuous improvement across multiple concurrent initiatives.

Design, build, deploy, and scale Python-first backend services, REST APIs, data pipelines, and cloud-native applications on GCP. Maintain and enhance Java services, integrate AI and LLM capabilities, modernize infrastructure, and ensure application security, reliability, and high test coverage. Collaborate with product, data, and infrastructure teams while conducting code reviews and documenting technical solutions.

Lead end-to-end technology projects in healthcare from planning through implementation. Coordinate Engineering, Product, QA, Infrastructure, and business teams; manage schedules, budgets, resources, risks, dependencies, and stakeholder communications; facilitate Agile ceremonies; ensure quality, compliance, documentation, and successful delivery; and drive continuous improvements across project processes and collaboration.

Principal Data Engineer responsible for developing and supporting Databricks pipelines, integrating heterogeneous healthcare data sources, modeling unified data products, and ensuring data quality and availability. The role partners with business stakeholders, product teams, data engineers, and clinical leaders to gather requirements, create datasets, support ad hoc analytics, enable machine learning and AI use cases, and assist with acquisition integrations. Extensive healthcare data, cloud, SQL, PySpark, and Python experience is required.

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.

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.