AI Developer

American Technology Consulting (ATC) is a service-first tech company dedicated to helping businesses unlock their full potential through innovative technology solutions. We empower organizations to leverage data for smarter decisions and meaningful impact. At ATC, we foster a culture of growth and invite passionate individuals to join our team, contribute to impactful projects, and excel as data-driven problem solvers. We embrace diversity and welcome candidates from all educational and professional backgrounds, including recent Master’s graduates without prior technical experience.

We are seeking a skilled AI Developer to design, build, and deploy autonomous AI agents from scratch. This role involves creating intelligent systems that can perceive environments, make decisions, and execute actions in real-world or simulated scenarios. You will leverage machine learning, Python, and specialized frameworks like Lang Chain and Lang Graph to develop scalable AI agents for applications such as automation, robotics, virtual assistants, or multi-agent simulations.

• Architect and implement AI agents from the ground up using frameworks such as Lang Chain for chaining LLMs and tools, and Lang Graph for stateful, graph-based agent workflows, including perception modules (e.g., using computer vision or NLP), decision‑making logic (e.g., via reinforcement learning or planning algorithms), and action execution components.
• Develop and train machine learning models using frameworks like Tensor Flow, PyTorch, or Scikit‑learn to enable agent learning and adaptation, integrating with Lang Chain/Lang Graph for advanced agent orchestration.
• Integrate AI agents with external systems, APIs, databases, and environments (e.g., simulation tools like OpenAI Gym or real-world interfaces), ensuring seamless tool usage and memory management via Lang Chain components.
• Optimize agents for performance, scalability, and robustness, including handling edge cases, ethical considerations, and safety protocols within graph‑structured agent designs.
• Collaborate with cross‑functional teams (e.g., data scientists, software engineers) to iterate on agent designs based on feedback and testing.
• Conduct experiments, simulations, and evaluations to refine agent behaviors and ensure reliability in production.
• Document code, architectures, and methodologies for reproducibility and team knowledge sharing.
• Stay current with advancements in AI agent technologies, such as large language models (LLMs), multi‑agent systems, and emerging frameworks like Lang Chain and Lang Graph.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Proficiency in Python programming, with strong experience in ML libraries (e.g., Tensor Flow, PyTorch, Num Py, Pandas) and agent‑specific tools (e.g., Lang Chain, Lang Graph, Auto Gen, RLlib, Hugging Face Transformers).
• Hands‑on experience building AI agents from scratch using Lang Chain for tool integration and agent chains, Lang Graph for multi‑step reasoning and state management, including reinforcement learning, state machines, graph‑based planning, or evolutionary algorithms.
• Solid understanding of data structures, algorithms, software engineering principles, and version control (e.g., Git).
• Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying agents, and tools like Docker/Kubernetes for containerization.
• Strong problem‑solving skills, with the ability to debug complex systems and work in agile, fast‑paced environments.
• Excellent communication skills to articulate technical designs and collaborate effectively.

• Experience with specialized domains like natural language processing (NLP), computer vision, robotics (e.g., ROS), or game AI, integrated with Lang Chain/Lang Graph.
• Knowledge of big data tools (e.g., Spark, Hadoop) or databases (SQL/No
  
  SQL) for handling large‑scale agent data.
• Prior work with multi‑agent systems, ethical AI, or real‑time applications using advanced frameworks.
• Contributions to open‑source AI projects or a portfolio demonstrating agent‑building expertise (e.g., Git Hub repos showcasing Lang Chain/Lang Graph implementations).