- Company Name
- Unity Advisory
- Job Title
- Full Stack Engineer
- Job Description
-
Job Title: Full Stack Engineer
Role Summary:
Engineer end‑to‑end software solutions for Unity Advisory’s internal AI platform. Own features from concept to production, focusing on scalable backend services, modern front‑end UI, and seamless AI/data integration.
Expectations:
- Deliver production‑grade, high‑availability systems in a fast‑moving, high‑ownership environment.
- Own the full development lifecycle: design, code, test, deploy, monitor, and iterate.
- Collaborate closely with AI, data, and product teams, translating business needs into technical solutions.
Key Responsibilities:
- Design, build, and maintain full‑stack applications that support internal AI workflows and tools.
- Develop scalable APIs, microservices, and data integrations for AI‑enabled features.
- Create intuitive, performant user interfaces for complex, data‑driven systems.
- Integrate AI components (ML models, inference services) into applications.
- Implement robust testing, CI/CD pipelines, and automated deployments in cloud/distributed environments.
- Optimize performance, reliability, scalability, and security of all stack layers.
- Document architecture, coding standards, and best practices; facilitate knowledge sharing.
- Troubleshoot and resolve production incidents, ensuring minimal downtime.
- Contribute to architectural decisions across application, platform, and integration layers.
Required Skills:
- 5+ years of full‑stack or backend‑heavy engineering experience.
- Proficiency in front‑end frameworks (React, Angular, Vue) and backend languages (Node.js, Python, Go, Java).
- Experience building REST/GraphQL APIs, microservices, and data pipelines.
- Strong understanding of web application architecture, data flow, and system integration.
- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Experience with automated testing (unit, integration, end‑to‑end) and CI/CD tooling (GitHub Actions, Jenkins, GitLab CI).
- Knowledge of AI/ML integration concepts (model serving, inference APIs).
- Solid problem‑solving, debugging, and performance optimization skills.
- Excellent communication; ability to work with technical and non‑technical stakeholders.
- Comfortable with rapid change and evolving requirements in a high‑growth setting.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent experience).
- Relevant certifications (e.g., AWS Certified Developer, Google Cloud Professional DevOps Engineer) are a plus.