As an Agentic AI Developer, you will contribute to the development, deployment, and maintenance of agentic AI solutions, ensuring they are robust, scalable, and meet business needs. This role involves close collaboration with cross-functional teams to analyze data, implement AI solutions, and deliver insights that drive business value.

Data Preparation and Analysis:

Conduct Exploratory Data Analysis (EDA) on various datasets to extract meaningful insights.
Preprocess and prepare data for AI solutions, ensuring effective management of data using vector databases for efficient data retrieval.

Agentic Solution Development and Maintenance:

Develop and deploy agentic AI solutions with a focus on performance and scalability.
Debug AI pipelines and processes to resolve issues efficiently.
Explain the mechanics and functionality of agentic AI solutions to stakeholders, ensuring clear communication of technical concepts.

Programming and Infrastructure:

Write high-quality, maintainable Python code, following best practices for performance and readability.
Develop unit tests using PyTest to ensure the reliability and robustness of your code.
Maintain and optimize infrastructure using Docker for containerization and easy deployment.

Collaboration and Communication:

Conduct code reviews to maintain quality across the development team.
Analyze business feedback to refine agentic solutions and processes to better meet business goals.
Write and optimize prompts for large language models (LLMs) to enhance their applications in AI solutions.

Qualifications Must-Have Skills:

Strong proficiency in Python and familiarity with best programming practices for readability, maintainability, and performance.
Hands-on experience with PyTest for writing unit tests and ensuring code reliability.
Competence in developing and maintaining agentic AI solutions.
Understanding of NoSQL and vector databases for efficient data management.
Familiarity with large language models (LLMs) and natural language processing (NLP) techniques.

Technical Knowledge:

In-depth understanding of the inner workings and characteristics of agentic AI solutions.
Strong foundation in statistics and mathematics that underpin AI models.
Experience with data preparation and techniques for AI consumption, including EDA.

Core Competencies:

Ability to independently understand, analyze, and solve complex problems in a structured manner.
Creative thinking to design innovative and working solutions to problems.
Organizational skills to manage tasks and deliverables efficiently while meeting deadlines.
Clear communication skills, both written and verbal, for collaborating with stakeholders and team members.

Ideal Candidate Traits

Proactive: Takes initiative and demonstrates ownership of tasks and challenges.
Curious: Passionate about continuous learning and staying updated on the latest AI developments.
Creative: Excels at generating new ideas and finding non-standard solutions to problems.
Comfortable with Ambiguity: Thrives in uncertain environments and can adapt to changing requirements.
Learning on the Job: Eager to learn new technologies and methodologies as needed.

Technology Stack

Programming: Python
Testing Frameworks: PyTest
Infrastructure: Docker
Data Management: SQL, Vector Databases
Agentic AI Solutions: Familiarity with advanced AI models and agentic frameworks.