Artificial Intelligence Engineer - LLM/RAG

Description :

- Design, train, and deploy AI-driven systems and intelligent agents that enhance business workflows and user experiences.

- Develop and optimize LLM-based solutions using models such as GPT-4, Claude, Llama 2, and Mistral.

- Architect multi-model orchestration frameworks and implement intelligent model routing and decision workflows.

- Build retrieval-augmented generation (RAG) pipelines integrating vector databases for contextual knowledge retrieval.

- Implement self-assessment, reflection, and feedback loops to improve model reasoning and output quality.

- Utilize frameworks such as LangChain, LlamaIndex, CrewAI, or OpenAI function calling to build modular and reusable agentic systems.

- Develop AI evaluation dashboards to measure performance metrics such as win-rate, response confidence, and perplexity.

- Collaborate with data scientists, ML engineers, and product teams to ensure scalable and maintainable AI solutions.

- Implement safety, ethical, and fallback mechanisms for responsible AI deployment.

- Contribute to research and experimentation on emerging trends in AI reasoning, orchestration, and agentic intelligence.

Required Skills & Qualifications :

- 38+ years of experience in AI Engineering, Machine Learning, NLP, or related fields.

- 23+ years of hands-on experience building AI agents or multi-model orchestration architectures.

- Proficiency in Python, OpenAI SDK, LangChain, LlamaIndex, and Hugging Face libraries.

- Strong understanding of LLM architectures, fine-tuning, and inference optimization techniques.

- Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, ChromaDB).

- Deep understanding of retrieval-augmented generation (RAG) and prompt engineering strategies.

- Knowledge of CI/CD for AI models, cloud AI platforms (AWS, Azure, GCP), and containerization tools (Docker, Kubernetes).

- Experience designing AI evaluation frameworks and monitoring tools for performance tracking.

- Familiarity with LLM safety, bias mitigation, and ethical AI development practices.

Preferred Qualifications :

- Masters degree in Computer Science, AI, Machine Learning, or a related field.

- Experience working with OpenAI APIs, Anthropic, or Meta LLM ecosystems.

- Exposure to AutoGPT, BabyAGI, or CrewAI frameworks for autonomous agent development.

- Background in data pipelines, MLOps, or cloud-based AI orchestration.