Software engineer

Design, deploy, and scale robust workflow models utilizing end-to-end task Automation frameworks.

Architect scalable Data engineering workflows and build Retrieval-Augmented Generation (RAG) pipelines for intelligent data querying.

Implement system Observability tools, telemetry metrics tracking, and real-time operational log monitoring systems.

Execute thorough code optimization, resource usage checks, and systematic Performance tuning runs across platforms.

Manage codebase branching, track software release versions, and govern team repository merges using GIT and Version control systems.

Collaborate cross-functionally with data science and infrastructure squads to optimize computational system speed.

Maintain clear technical documentation, architectural diagrams, and automated deployment runbooks.

Degree in Computer Science, Information Technology, Data Engineering, or a technical quantitative field.

1-3 Yrs of professional software engineering or data engineering experience, perfect for junior to mid-level specialists.

Practical hands-on exposure constructing RAG architectures, configuring automated pipelines, and managing Git repositories.

Solid structural understanding of application performance monitoring, system logging baselines, and data architecture patterns.

High learning agility paired with strong analytical troubleshooting skills and collaborative team communication.