- Experience: 10 – 15 years of full-stack software engineering experience in an enterprise or production environment.

- Design Patterns: Deep understanding of object-oriented and functional design patterns, with a proven ability to write clean, modular, and testable code.

- Polyglot Programming: Proficiency in a diverse set of programming languages:

- Python (for data science, modeling, and scripting)

- Java (for enterprise-grade backend services)

- JavaScript / TypeScript (for full-stack integration and contemporary web frameworks)

- SQL (for complex data querying and relational database management)

- Shell Scripting (for system automation and environment configuration)

Cloud, DevOps &

- Infrastructure

- AWS Ecosystem: Extensive experience deploying, configuring, monitoring, and troubleshooting full-stack applications and ML workloads in Amazon Web Services (AWS) (e.g., SageMaker, ECS/EKS, Lambda, S3, and IAM).

- CI/CD Platforms: Hands-on experience orchestrating automated build, test, and deployment pipelines using the GitLab platform.

Data Engineering &

- Governance

- Data Management: Strong grasp of modern data ingestion, ETL/ELT pipelines, and data persistence strategies, including relational (SQL),



non-relational (NoSQL), and search indexing technologies.

- Data Security: Solid understanding of best practices for data protection, data minimization, and data classification.

Next-Generation AI &

- Vibe-Coding Practices

- AI-Assisted Tooling: Practical experience utilizing AI-assisted coding platforms (e.g., Cursor, GitHub Copilot, Windsurf) to optimize development velocity.

- Vibe-Coding &
- Context Engineering:

Advanced understanding of AI-driven development paradigms ("vibe-coding"), including context window management, prompt structuring, iterative refinement, and the implementation of strict validation guardrails to prevent silent code failures or security vulnerabilities.

Soft Skills &

- Professional Attributes

- Technical Translation: Exceptional communication skills with a proven track record of presenting technical topics, model metrics, and architectural decisions to non-technical business clients.

- Collaborative Leadership: Strong peer-review skills, with a focus on fostering a collaborative, high-quality engineering culture through constructive feedback on merge requests.

📌 Senior Data Scientist & Machine Learning Engineer (Bengaluru)
🏢 Trigent Software
📍 Bengaluru