Lead the architecture and development of AI-powered, distributed systems that meet enterprise-grade performance and security standards.
Leverage AI tools for code generation, architectural design, and documentation to accelerate delivery and improve quality.
Design, build, and maintain services using Python, Java, and Node.js, following clean-code and secure design principles.
Develop agentic AI-based tools, domain-specific copilots, and developer productivity enhancements.
Collaborate with cross-functional teams to define modular, scalable, and compliant architecture patterns.
Conduct technical design reviews and produce detailed documentation, including system specifications, API docs, and architecture diagrams.
Integrate AI solutions into CI/CD pipelines, ensuring observability, automated testing, and deployment standards are met.
Implement robust monitoring and performance engineering practices to maintain high-quality deployments.
Continuously evaluate emerging AI technologies and integrate them into development workflows for maximum impact.
Champion best practices in security, automation, and performance optimization across the organization.

Qualifications :

8+ years in software engineering with full-stack or backend development in Python, Java, and/or Node.js.
3+ years with AI tools for development, prototyping, or documentation tasks.
Experience with cloud-native development and containerized deployment (Docker, Kubernetes).
Knowledge of AI integration patterns, vector stores, prompt engineering, and RAG pipelines.
Ability to design software architecture using sequence diagrams, ERDs, data models, and threat models.
Comfortable with Gen AI-first environments and working with remote Agile teams.

Preferred Qualifications

Experience building AI copilots or developer tools using OpenAI/Claude SDKs, LangChain, or similar frameworks.
Experience working in a fast-paced, AIDLC environment, with a strong understanding of CI/CD practices.
Familiarity with GitHub Actions, Argo Workflows, Terraform, and monitoring/observability tools.
Containerization and Orchestration: Proficiency in Docker and Kubernetes for containerization and orchestration.
Cloud Platforms: Experience with cloud computing platforms such as AWS, Azure, or OCI Cloud.