Data & AI - AI Engineer

Job Description:

Job Description – Lead AI Engineer / Architect (LLMs, RAG, RL, Azure AI)
Role Overview
We are seeking an experienced Lead AI Engineer / Architect with expertise in transformer-based architectures, fine-tuning, reinforcement learning, and agent-based AI systems. The ideal candidate will have 10+ years of IT experience with a strong focus on LLMs, applied machine learning, and cloud AI platforms. This role involves designing and deploying enterprise-grade AI solutions leveraging LLMs (GPT, LLaMA, Mistral, Claude), retrieval-augmented generation (RAG), and reinforcement learning techniques while providing technical leadership to engineering teams.
Key Responsibilities
Architect and implement solutions using large language models (GPT, LLaMA, Mistral, Claude) for enterprise use cases.
Design and optimize retrieval-augmented generation (RAG) pipelines for knowledge-grounded AI applications.
Develop and deploy fine-tuned/custom models for domain-specific tasks.
Agent Frameworks & Orchestration
Build intelligent AI agents using frameworks such as LangChain, LlamaIndex, CrewAI, and AutoGen.
Integrate LLM agents with external APIs, databases, and enterprise systems.
Define prompt engineering strategies to optimize reliability, interpretability, and task success rates.
Reinforcement Learning & Optimization
Apply Q-learning, policy gradient methods, and RLlib for agent training and continuous learning.
Experiment with RLHF (Reinforcement Learning with Human Feedback) for fine-tuning LLMs.
Optimize inference and training pipelines for performance and cost efficiency.
Leadership & Collaboration
Play the role of Tech Lead / AI Architect, guiding engineers and data scientists on AI/LLM best practices.
Collaborate with product teams, business stakeholders, and cloud engineers to deliver AI-powered solutions at scale.
Mentor junior engineers in transformer models, prompt engineering, and reinforcement learning.
Cloud & MLOps
Deploy AI models using Azure AI Services, Azure Machine Learning, and CI/CD pipelines.
Implement MLOps frameworks for model versioning, monitoring, and continuous improvement.
Ensure governance, security, and compliance in AI deployments.
Required Skills & Qualifications
10+ years of IT experience, with relevant experience in AI/LLMs and reinforcement learning.
Strong expertise in:
Transformer architectures (GPT, LLaMA, Mistral, Claude)
Fine-tuning, prompt engineering, RAG
Agent frameworks (LangChain, LlamaIndex, CrewAI, AutoGen)
Reinforcement learning (Q-learning, policy gradients, RLlib)
Hands-on with Python, PyTorch/TensorFlow, and ML frameworks.
Experience with Azure AI (Azure AI Engineer Associate certified).
Proven ability to lead, mentor, and deliver enterprise AI solutions.
Preferred Skills
Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus).
Knowledge of evaluation frameworks for LLMs (e.g., benchmark datasets, automated evaluation).
Exposure to multi-agent collaboration systems and advanced orchestration.
Understanding of ethical AI, bias mitigation, and model interpretability.

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