Full Job Description
Position Description:
VSSE IT is seeking an exceptionally skilled and forward-thinking Senior Software Engineer who embraces Lean, Agile practices and uses AI to accelerate delivery of innovative end-to-end full stack software solutions that integrate enterprise data platforms and PLM systems through MCP servers. As a key architect and implementer, you will work across the entire software stack from front-end UI to backend services to cloud infrastructure and integrating AI enabled data platforms while also bringing domain familiarity with PLM ecosystems and engineering data platforms. Key Responsibilities End-to-End Application Development: Design, develop, test, and deploy full stack applications spanning UI, APIs, services, and data layers, owning features from concept through production. AI-Accelerated Software Development Across the SDLC: Use AI coding assistants and generative AI tools to accelerate software development, refactoring, debugging, documentation, and code reviews. Cloud-Native Engineering: Architect and implement scalable, resilient solutions on GCP 3.0, leveraging GCP services such as Cloud Run, Cloud Functions, App Engine, GKE, Cloud Storage, Pub/Sub, Firestore, BigQuery, Cloud SQL, Secret Manager, Cloud Build, Artifact Registry, and Cloud Monitoring, as applicable. Frontend Development: Build responsive, intuitive, and performant user interfaces using Angular architecture patterns, RxJS, NgRx or other state management approaches, and frontend performance optimization. Backend Development: Develop robust backend services and APIs using Spring (Java) and Node.js, ensuring scalability, security, and maintainability. Data Modeling & Workflows: Translate complex engineering data structures (BOMs, part/document lifecycle data) into usable application data models and workflows. API Design & Microservices: Design and implement RESTful/GraphQL APIs and microservices that support integration across PLM, MCP, and internal systems. MCP Server Integration: Develop and maintain integrations with MCP (Model Context Protocol) servers that house engineering data artifacts, ensuring reliable, secure, and performant data retrieval and orchestration. DevOps & CI/CD: Deploy infrastructure components using Terraform, orchestrated via Tekton pipelines. Implement CI/CD pipelines using Tekton and Github Actions. Code Quality & Best Practices: Champion clean code, automated testing, code reviews, and secure coding practices across the team. Cross-Functional Collaboration: Work closely with product managers, architects, and engineering data stakeholders to translate business requirements into technical solutions. Troubleshooting & Support: Diagnose and resolve complex integration and performance issues across distributed systems. Mentorship: Provide technical guidance and mentorship to junior/mid-level engineers.
Skills Required:
GCP Cloud Run, PostgreSQL, AIPGEE, GCP, Node.js, Angular, Spring Boot, REST APIs, React, Java, Microservices, Agile Software Development, Artificial Intelligence & Expert Systems, Big Query
Skills Preferred:
Integration, Teamcenter
Experience Required:
Senior Engineer Exp: Prac. In 2 coding lang. or adv. Prac. in 1 lang.; guides. 10+ years in IT; 8+ years in development
Education Required:
Bachelor's Degree
Additional Information:
Hybrid Position / 4 days onsite Required Skills & Qualifications: Proven experience of 10+ years as a Senior Software Engineer with Full Stack expertise with a strong portfolio of delivered projects. Deep proficiency in Java and extensive experience with the cloud native architecture and applications. Experience with microservice architecture and hands-on experience with building and consuming RESTful APIs, FAST APIs and Stream APIs. Hands-on experience with SQL, PostgreSQL, including table design, creation, and modification. Experience integrating with PLM products - Teamcenter and 3DX Strong practical experience deploying and managing applications on Google Cloud Platform (GCP). This could include experience with services like Cloud Run, Compute Engine, Cloud Storage, Firestore etc. Frontend: Angular, TypeScript, HTML, CSS/SCSS, RxJS, NgRx, Angular Material or similar component libraries Backend: Node.js, Java, Python, Spring Boot, NestJS, Express, REST APIs, microservices Cloud: Google Cloud Platform, Cloud Run, GKE, Cloud Functions, Cloud Storage, BigQuery, Pub/Sub, Cloud SQL, Firestore DevOps: Git, Docker, CI/CD, Cloud Build, Artifact Registry, Kubernetes, automated deployments AI/LLM: AI coding assistants, prompt engineering, LLM APIs, RAG, embeddings, vector databases, agentic workflows Engineering Practices: Agile, secure coding, API design, observability, documentation, production support
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