Technical Architect – Enterprise Applications
Quadance Technologies
- Thiruvananthapuram, Kerala
- Permanent
- Full-time
- Lead the architectural design and development of enterprise-level applications and AI/ML solutions.
- Collaborate with business and technical stakeholders to translate requirements into scalable and maintainable architectures.
- Design and implement end-to-end solutions with a focus on performance, security, and maintainability.
- Provide technical leadership and mentoring to development teams.
- Conduct code reviews, enforce best practices, and ensure adherence to architectural standards.
- Participate in technical discussions with client teams, providing guidance and strategic recommendations.
- Oversee integration of AI/ML components, with a strong emphasis on RAG-based solutions.
- Evaluate emerging technologies and drive innovation in architecture and solutioning.
- Work closely with DevOps and QA teams to support CI/CD, automated testing, and deployment practices.
- 810 years of overall experience in software development and architecture.
- Proven experience designing and building large-scale enterprise applications.
- Proficient in either Python or C# .Net, with strong coding and debugging skills.
- Solid understanding of architectural patterns (e.g., microservices, event-driven, layered architecture).
- Hands-on experience with cloud platforms (e.g., AWS, Azure, or GCP).
- Strong experience working with databases (SQL and NoSQL), APIs, and integration patterns.
- Exposure to AI/ML solutions, especially RAG-based architectures (e.g., combining LLMs with vector databases, context-aware search).
- Familiarity with vector databases like FAISS, Pinecone, or Weaviate.
- Strong understanding of LLMs, embeddings, prompt engineering, and data pipelines.
- Excellent communication and interpersonal skills.
- Experience interacting with client stakeholders in technical discussions.
- Ability to manage technical teams, assign tasks, and ensure high-quality deliverables.
- Experience with containerization (Docker, Kubernetes).
- Exposure to MLOps and deployment of AI models in production.
- Experience in Agile/Scrum methodologies.
- Certifications in cloud architecture (AWS Solutions Architect, Azure Architect, etc.) or AI/ML will be a plus.
Expertia AI Technologies