Agentic AI Developer

Tek Spikes is seeking an innovative Agentic AI Developer to join our forward-thinking team. In this role, you will be responsible for the development and implementation of agent-based AI models that enhance decision-making and automation across various applications. You will work closely with data scientists, product managers, and software engineers to design systems that can autonomously perform tasks and interact with users in real-time.

Key Responsibilities:

• Design, develop, and deploy intelligent agent systems that can autonomously make decisions and learn from their environment.
• Implement machine learning algorithms tailored for agent-based systems to improve performance over time.
• Collaborate with cross-functional teams to integrate agent technologies into existing products and workflows.
• Conduct research to explore and adopt cutting-edge techniques in autonomous systems and artificial intelligence.
• Participate in brainstorming and problem-solving sessions to understand user requirements and tailor solutions accordingly.
• Document development processes, methodologies, and systems to support future transparency and maintenance.
• Stay updated on trends in AI and emerging technologies relevant to agent-based development.

Requirements

Qualifications:

- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.

- 9+ years of experience in AI development, specifically with a focus on agent-based systems.

- Solid understanding of machine learning concepts and algorithms, with experience using frameworks such as TensorFlow or PyTorch.

- Proficiency in programming languages such as Python, Java, or C#.

- Experience with software development methodologies and best practices, including version control and testing.

- Excellent analytical skills and the ability to approach complex problems creatively.

- Strong communication skills, with the ability to convey technical concepts to both technical and non-technical audiences.

Preferred Skills:

- Familiarity with reinforcement learning and multi-agent systems.

- Knowledge of natural language processing (NLP) and computer vision technologies.

- Experience with cloud computing platforms and AI services (AWS, Google Cloud, Azure).