Applix
Website:
applix.ai
Job details:
About Job
Applix is looking for a highly skilled Senior Software Engineer – Platform & Services to design, develop, and optimize scalable data-as-a-service capabilities within a Digital Manufacturing & Supply Chain Platform.
The role focuses on building secure, high-performance APIs, microservices, and event-driven services that expose curated data from enterprise applications, IoT platforms, and analytical systems to applications, dashboards, and simulation environments.
The ideal candidate will work closely with Data Engineering, Cloud, Platform, Architecture, and Product teams to transform enterprise and IoT data into reliable, observable, secure, and production-ready services supporting real-time insights, predictive analytics, and digital-twin use cases.
Key Responsibilities
- Design, develop, and maintain RESTAPIs, gRPC, and GraphQL APIs for real-time and batch data consumption.
- Build scalable microservices and event-driven services using modern backend technologies.
- Develop service components that expose curated datasets from enterprise systems, IoT platforms, and analytical data sources.
- Collaborate with Data Engineering teams on data pipelines, data contracts, data quality, governance, and integration requirements.
- Implement enterprise-grade authentication, authorization, RBAC, OAuth2, and JWT-based security controls.
- Design and optimize services for high availability, scalability, reliability, and low-latency performance.
- Contribute to API lifecycle management, including API versioning, documentation, monitoring, observability, and governance.
- Containerize and deploy services using Docker and Kubernetes across cloud-native environments.
- Develop and maintain CI/CD pipelines and automated deployment workflows using GitHub Actions and related DevOps tools.
- Implement Infrastructure as Code (IaC) and support automated cloud infrastructure provisioning and configuration.
- Integrate messaging and event-streaming technologies such as Kafka or Azure Event Hubs.
- Implement monitoring and observability using tools such as Prometheus, Grafana, and OpenTelemetry.
- Troubleshoot production issues, perform root-cause analysis, and implement preventive and corrective measures.
- Work with architects and product teams to ensure service designs align with platform architecture, security, scalability, and business requirements.
- Participate in Agile ceremonies, backlog planning, estimation, and delivery using Azure DevOps (AzDO) Boards.
- Maintain high standards of code quality, automated testing, documentation, security, and DevOps practices.
- Leverage AI-assisted development and AI agents where appropriate to accelerate API, microservice, testing, and platform engineering activities.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline.
- 5–8 years of professional software engineering experience, with strong hands-on backend/platform development experience.
- Strong experience developing and integrating REST APIs and working knowledge of gRPC and/or GraphQL.
- Solid understanding of microservices architecture, distributed systems, and service-oriented architecture.
- Strong programming experience in Java with Spring Boot and/or Python.
- Hands-on experience with Docker and Kubernetes.
- Practical experience with at least one major cloud platform, preferably AWS or Azure.
- Experience with Kafka, Azure Event Hubs, or similar messaging/event-streaming platforms.
- Hands-on experience building and maintaining CI/CD pipelines, preferably using GitHub Actions.
- Experience with cloud-native application deployment and production operations.
- Good understanding of API security, authentication, authorization, RBAC, OAuth2, and JWT.
- Experience working with Azure DevOps Boards in an Agile development environment.
- Strong problem-solving, debugging, communication, and cross-functional collaboration skills.
Preferred Qualifications
- Experience with API Gateways, developer portals, API management platforms, and API usage analytics.
- Experience with data virtualization, semantic layers, or enterprise analytics platforms.
- Hands-on experience with Prometheus, Grafana, OpenTelemetry, or similar observability technologies.
- Understanding of data integration, orchestration, and enterprise data-service patterns.
- Experience working with IoT, manufacturing, supply chain, industrial systems, or Industry 4.0 platforms.
- Exposure to digital twins, simulation platforms, OpenUSD, or NVIDIA Omniverse.
- Experience building services supporting predictive maintenance, dynamic scheduling, real-time analytics, or simulation-driven workflows.
- Contributions to open-source projects, technical publications, or platform engineering initiatives are a plus.
- Experience using AI coding assistants or AI agents to accelerate software/API development, testing, troubleshooting, and documentation.
Technical Skills
Backend: Java, Spring Boot, Python
APIs: REST, gRPC, GraphQL
Architecture: Microservices, Distributed Systems, Event-Driven Architecture
Cloud: AWS, Azure
Containers: Docker, Kubernetes
Messaging: Kafka, Azure Event Hubs
DevOps: GitHub Actions, CI/CD, Infrastructure as Code
Security: OAuth2, JWT, RBAC, Authentication & Authorization
Observability: Prometheus, Grafana, OpenTelemetry
Agile/ALM: Azure DevOps Boards
Data & Platform: Data APIs, Data Contracts, Data Integration, Data Virtualization
Emerging/Preferred: OpenUSD, NVIDIA Omniverse, Digital Twins, AI Agents
Ideal Candidate Profile
The ideal candidate is a hands-on senior backend/platform engineer who can independently design and deliver production-grade APIs and microservices while working effectively across Data Engineering, Cloud, DevOps, Architecture, and Product teams.
Candidates should demonstrate strong practical engineering depth rather than only theoretical knowledge, particularly in API development, microservices, cloud deployment, Kubernetes, event-driven architecture, security, and production troubleshooting.
Click on Apply to know more.
