Process Manager

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.