Key Responsibilities:
- AI and Machine Learning Model Design: Lead the design, development, and optimization of Batch LLM (Large Language Models) and GenAI-driven applications, ensuring performance, scalability, and robustness.
- Prompt Engineering: Develop and refine AI prompt flows to enhance the effectiveness and accuracy of LLMs, OpenAI models, and other AI-driven systems.
- Python Development: Write clean, efficient, and maintainable Python code for AI, data processing, and backend services.
- REST API Development: Design, develop, and integrate REST APIs to interact with AI models and third-party systems.
- Database Management: Work with SQL databases to manage and query data for AI systems and applications.
- Version Control & CI/CD: Utilize Git for version control and CI/CD pipelines for automated deployment processes.
- Collaboration: Work closely with cross-functional teams, including data scientists, engineers, and product managers, to design and deploy AI-powered solutions.
- Documentation: Create clear, detailed documentation for code, model workflows, and system architecture.
Skills and Qualifications:
- Required Skills:
- Python: Proficient in Python programming for AI model development, data analysis, and backend services.
- SQL: Strong knowledge of SQL for querying, managing, and manipulating data.
- GenAI Prompting: In-depth experience in designing and optimizing prompts for GenAI applications, particularly in the context of LLMs (e.g., OpenAI).
- REST API: Experience in building and consuming REST APIs for seamless integration between AI models and other systems.
- Pandas: Expertise in using Pandas for data manipulation, analysis, and processing in AI workflows.
- Batch LLM Design: Hands-on experience in designing and deploying batch processing workflows for large-scale LLMs.
- Git & CI/CD: Strong experience with version control using Git and continuous integration/deployment (CI/CD) practices.
- Communication: Excellent verbal and written communication skills to effectively communicate with both technical and non-technical stakeholders.
- Good to Have:
- Prompt Flow: Knowledge of designing efficient prompt flow systems for complex AI tasks.
- Langchain: Familiarity with Langchain or similar frameworks for building end-to-end AI systems, particularly with LLMs.
Desired Experience:
- 6+years of hands-on experience in Python development, with a focus on AI/ML and GenAI technologies.
- Proven experience with LLMs, prompt engineering, and related technologies, such as OpenAI, Langchain, etc.
- A track record of deploying AI-driven systems and solutions at scale.
- Strong problem-solving abilities and experience in debugging complex systems.
