Artificial Intelligence Engineer - LLM/NLP

About The Role

Key Responsibilities

• Design, build, and fine-tune AI/ML models with a focus on Large Language Models (LLMs) and NLP applications.
• Implement prompt engineering strategies for enhanced model performance and precision.
• Work on retrieval-augmented generation (RAG), semantic search, text summarization, and classification tasks.
  

Engineering & Deployment

• Develop scalable APIs and integrate AI models into production environments.
• Deploy and manage backend AI services on cloud platforms such as AWS, Azure, or Google Cloud (GCP).
• Ensure optimized model inference performance and reliability in real-world applications.
  

Collaboration & Integration

• Partner with data scientists, product teams, and software engineers to translate business requirements into scalable AI-driven solutions.
• Contribute to system architecture discussions and provide technical recommendations for AI integration.
• Collaborate in building conversational AI tools including chatbots, voice assistants, and virtual agents.
  

Research & Innovation

Required Skills & Experience

• 3+ years of experience in software development with a strong focus on AI/ML projects.
• Proven expertise in Python programming and related AI/ML libraries (TensorFlow, PyTorch, Transformers, etc.).
• Hands-on experience with LLMs (e.g., OpenAI, Claude, Llama, Gemini) and prompt engineering techniques.
• Solid understanding of NLP pipelines, including tokenization, embeddings, and semantic understanding.
• Experience with LangChain, RAG architectures, or vector databases (FAISS, Pinecone, Weaviate, etc.).
• Proficiency in API design, development, and integration.
• Practical experience deploying AI applications on AWS, Azure, or GCP.
• Strong grasp of backend architecture, version control (Git), and CI/CD workflows.
• Excellent analytical, problem-solving, and communication skills.
  

Nice To Have

• Experience with MLOps tools (e.g., MLflow, Kubeflow, Vertex AI, SageMaker).
• Familiarity with model lifecycle management, monitoring, and retraining pipelines.
• Prior experience developing chatbots, voice bots, or virtual assistants.
• Knowledge of containerization (Docker, Kubernetes) and microservice architectures.
  

• Work on cutting-edge AI solutions that have tangible real-world impact.
• Be part of a collaborative, innovative, and fast-paced environment.
• Opportunity for continuous learning and professional growth.
• Flexible work culture with an emphasis on creativity, ownership, and teamwork.