Artificial Intelligence Engineer

Location-

Working Days-

AI Engineer

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 behavior in agents.

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 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

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