Python + Gen AI
Experience: 7+ years to 9years
Model: Work from Home
Python + Gen AI
Main Responsibilities
- LLM Application Development: 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.
- Working with RAG frameworks: 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 latest research: Given that this is a fast evolving field, its important to keep track of the latest advancements in fine-tuning, RLHF, and prompt engineering advancements such as DSPy.
- System Design & Architecture: Translate high-level product requirements into scalable, modular software designs that adhere to modern design principles, microservices architecture, and cloud-native best practices.
- Testing & Integration: Develop comprehensive test suites (unit, integration, and end-to-end) to ensure code quality, maintaining a minimum of 90% test coverage. Integrate solutions across systems, perform bug fixes, and conduct rigorous quality assurance.
- Collaboration & Mentorship: 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.
- Agile Delivery: Work in an agile environment, planning and executing sprints, meeting strict deadlines, and efficiently handling production issues across multiple time zones.
- CI/CD & Version Control: Employ CI/CD pipelines (GitHub Actions or similar) and maintain code versioning in GitHub for seamless, frequent releases.
Key Result Area
- LLM Solutions Delivery: Launch production-ready LLM-based agentic applications on schedule, ensuring quality and scalability.
- Quality & Automation:Achieve high-quality daily releases and ensure automation covers at least 90% of the test cases.
- Risk Management & Reporting:
Proactively identify risks and effectively communicate them to stakeholders. Maintain transparent and timely reporting of development progress and metrics.
Skillsets
· 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.
Qualifications & Experience
· Engineering experience in a tier-1 organization for a period of 8 to 15 years.
· Strong proficiency in Python programming language (minimum 5 years)
· Minimum 6 months experience working with GenAI applications