Associate Agentic AI Engineer

We are seeking an enthusiastic and promising Associate Agentic AI Engineer to join our growing AI CoE. This is an excellent opportunity for an early-career engineer passionate about artificial intelligence and autonomous systems. In this role, you will contribute to the development, testing, and deployment of AI agents designed to perceive their environment, make decisions, and take actions. You will work under the guidance of senior engineers and architects, collaborating with Data Scientists and business stakeholders to build foundational components of innovative agentic solutions. This role offers a unique chance to learn and grow in the cutting-edge field of Agentic AI while contributing to impactful projects.

Your role:

AI Agent Development & Support:

• Assist in the development and implementation of AI agent components using established agentic AI frameworks (e.g., Google ADK, LangChain, AutoGen, CrewAI) and programming languages (primarily Python), under the guidance of senior team members.
• Support the integration of AI agents with enterprise systems, APIs, and data sources.
• Contribute to the development of core agent functionalities, such as natural language processing, basic reasoning with LLMs, and tool usage.
• Write clean, well-commented, and testable code with a focus on learning and applying best practices.

Collaboration & Learning:

• Work closely with senior engineers and AI Architects to understand technical designs and implement specific modules or features of AI agents.
• Collaborate with Data Scientists to help integrate data and model outputs into agent workflows.
• Actively participate in agile development processes, including sprint planning, daily stand-ups, and sprint reviews, focusing on learning and contribution.
• Engage in code reviews (both giving and receiving feedback) to improve code quality and learn from experienced team members.

Testing & Troubleshooting:

• Assist in developing and executing test cases for AI agent components, including unit tests and integration tests.
• Help troubleshoot and debug issues related to agent behavior and performance under supervision.
• Contribute to the documentation of agent functionalities and testing procedures.

Continuous Growth & Skill Development:

• Demonstrate a strong commitment to learning and staying updated with advancements in agentic AI, LLMs, machine learning, and software engineering.
• Actively seek opportunities to expand technical skills and knowledge within the AI CoE.
• Contribute to a positive and collaborative team environment. What you bring to the role:
• Bachelor's degree in computer science, artificial intelligence, machine learning, software engineering, or a related technical field.
• 0-2+ years of experience in software engineering, with a demonstrated interest and foundational knowledge in AI/ML development (internships, academic projects, or personal projects are valuable).
• Basic understanding of or keen interest in Agentic AI, autonomous agents, and Large Language Models (LLMs).

Some practical exposure is a plus, which could include Familiarity with or initial exploration of agentic AI concepts or frameworks (e.g. ADK, LangChain, AutoGen, or similar through coursework or self-study). Understanding of how LLMs (e.g., Gemini, GPT series, Claude, Llama models) can be used for tasks like text generation, understanding, or simple reasoning.

• Proficiency in Python and familiarity with common AI/ML libraries (e.g., scikit-learn, Pandas, NumPy).
• Solid grasp of fundamental software engineering principles and best practices (e.g., version control with Git).
• Basic understanding of API concepts and how to interact with them.
• Familiarity with data structures and algorithms.
• Exposure to cloud computing platforms (e.g., AWS, Azure, GCP including Google Vertex AI) is a plus.
• Strong problem-solving aptitude and a willingness to learn.
• Good communication skills and ability to work effectively as part of a team.

Preferred Qualifications & Experience:

• Master's degree in a relevant field.
• Internship experience focused on AI/ML development.
• Experience with building small projects using LLM APIs.
• Contributions to open-source projects or active participation in AI/ML communities.
• Familiarity with basic MLOps concepts.
• Exposure to containerization technologies (e.g., Docker).
• A portfolio of projects (e.

g., GitHub) demonstrating coding skills and AI/ML interest.