Python Developer – Gen AI

Job Description

Job Description:
• Architect, implement, and optimize Generative AI applications leveraging Large Language Models (LLMs).
• Quickly learn and adopt agentic frameworks (e.g., LangChain, LangGraph) to orchestrate LLM-based agents.
• Use techniques such as chunking, hybrid search, query translation, similarity search, vector DBs, evaluation metrics, and ANN algorithms.
• Monitoring performance: Using observability services such as Datadog for LLM Observability and analytics.
• Keep track of the latest advancements in fine-tuning, RLHF, and prompt engineering advancements such as DSPy.
• Translate high-level product requirements into scalable, modular software designs that adhere to modern design principles, microservices architecture, and cloud-native best practices.
• Develop comprehensive test suites (unit, integration, and end-to-end) to ensure code quality, maintaining a minimum of 90% test coverage.
• Collaborate with cross-functional stakeholders, including business analysts, product managers, and global development teams.
• Mentor junior engineers, guiding them through LLM-based solution design, implementation, and deployment.
• Work in an agile environment, planning and executing sprints, meeting strict deadlines, and efficiently handling production issues across multiple time zones.
• Employ CI/CD pipelines (GitHub Actions or similar) and maintain code versioning in GitHub for seamless, frequent releases.
• Launch production-ready LLM-based agentic applications on schedule, ensuring quality and scalability.
• Achieve high-quality daily releases and ensure automation covers at least 90% of the test cases.
• Proactively identify risks and effectively communicate them to stakeholders. Maintain transparent and timely reporting of development progress and metrics.

Requirements:
• Strong proficiency in Python programming language ( minimum 5 years )
• Minimum 6 months experience working with GenAI applications
• Strong communication skills since we work with a global team
• Leadership and Mentoring: Guiding and mentoring other engineers Providing technical expertise
• Experience with cloud platforms (e.g Azure, AWS).
• Knowledge of microservices architecture and containerization technologies (e.g., Docker, Kubernetes).
• Experience with RESTful APIs and API design principles.
• Understanding of database management systems (e.g., NoSQL, PostgreSQL).
• Proficiency with Git for version control.
• Version Control Systems: GitHub Managing code changes and collaborating with other team members Maintaining a history of code revisions.
• Continuous Integration/Continuous Deployment (CI/CD): Tools like GitHub Actions Integrating the automation into CI/CD pipelines
• Problem-Solving and Analytical Thinking: Designing efficient automation solutions/Framework Ability to identify and troubleshoot complex software defects
• Agile Methodologies: Agile methodologies such as Scrum or Kanban Planning for Iterative development cycles Manage frequent releases
• Risk Assessment and Mitigation: Ability to identify and mitigate risks related to software quality. Measure how well risks are documented and managed throughout the project.

Benefits: