Atologist Infotech is looking for an experienced and forward-thinking AI Engineer to help shape and scale our AI Agent Framework. This is a hands-on engineering role focused on building intelligent, modular agent systems that can reason, plan, and interact autonomously in real-world applications. You will work alongside a highly collaborative team to develop systems that leverage LLMs, contextual memory, and tool integration—delivering AI-native applications, not just traditional ML pipelines. Key Responsibilities AI Agent System Development--Design and implement agent-oriented systems that support task decomposition, memory handling, and contextual planning. Framework Engineering--Develop and extend our in-house AI Agent Framework with reusable components like tools, memory modules, and orchestration logic. Contextual Intelligence--Build and integrate vector search, semantic retrieval, and memory systems to enable long-term, goal-driven agent behaviour. Natural Language Interfaces--Connect LLMs (e.g., OpenAI, Anthropic) and NLU/NLP layers to enable natural task inputs and autonomous reasoning capabilities. API Engineering--Develop RESTful APIs using FastAPI, Flask, or Django to expose agent capabilities and integrate with other products. System Architecture--Design scalable, event-driven microservice architectures tailored for AI-native workloads and agent frameworks. Ethical AI--Prioritize responsible AI design with user safety, transparency, and privacy at the core. Required Skills & Qualifications Education--Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field. Python Proficiency--Strong software engineering skills in Python (3.x) with deep understanding of async programming, architecture design, and typing. AI/LLM Experience--Practical experience of 3 YEARS using LLMs for reasoning, prompt engineering, chaining, or building agent-like applications. Frameworks & Tools--FastAPI, Flask, or Django LangChain, LlamaIndex, or other agent frameworks Vector stores (e.g., FAISS, Weaviate, Pinecone) PostgreSQL, Redis, and event queues (e.g., Celery, RabbitMQ) Version Control & Testing--Proficient with Git workflows and writing tests using Pytest or similar. Bonus Skills (Nice-to-Have) Experience with autonomous agents, tool-calling, or memory-driven task systems Familiarity with cognitive architectures or symbolic reasoning Contributions to open-source AI frameworks or tooling
Job Title
Artificial Intelligence Engineer