AI / NLP Engineer

Role Overview

We are looking for an experienced AI / NLP Engineer to work on an advanced Agentic AI and Reasoning Platform focused on improving the performance, efficiency, scalability, and auditability of Large Language Models. The platform acts as a reasoning and orchestration layer over existing LLMs.

Key Responsibilities

• Design and develop scalable AI and NLP solutions using Python.
• Build and optimise LLM-powered applications and agentic workflows.
• Develop RAG, semantic search, NER, text-understanding, and knowledge-graph solutions.
• Create multi-step reasoning and AI orchestration pipelines.
• Integrate vector databases, embeddings, and retrieval systems.
• Build APIs and backend services for AI applications.
• Work with GPT, Claude, DeepSeek, Qwen, and other LLMs.
• Ensure the performance, scalability, reliability, and auditability of AI workflows.
• Participate in rapid prototyping and Gen AI product experimentation.

Requirements

• Strong hands-on Python development experience.
• Expertise in NLP, Generative AI, LLMs, RAG, and Agentic AI.
• Experience with TensorFlow, PyTorch, or Scikit-learn.
• Familiarity with LangChain, LangGraph, CrewAI, and multi-agent systems.
• Experience with MCP-based architectures.
• Experience with vector databases, embeddings, and semantic search.
• Experience with API development and backend integration.
• Familiarity with PostgreSQL or NoSQL databases.
• Experience with AI orchestration and reasoning frameworks.
• Preferred: Knowledge graphs and symbolic reasoning.
• Preferred: AI evaluation and prompt-engineering pipelines.
• Preferred: Workflow verification and orchestration-heavy AI applications.
• Preferred: AWS or other cloud platforms, Docker, MLOps, or LLMOps.
• Strong analytical and problem-solving abilities.
• Excellent communication and collaboration skills.
• Self-driven with a strong ownership mindset.
• Comfortable working in a fast-paced environment.
• Experience collaborating with globally distributed teams.