Overview
Skills
Job Details
Define & Design AI Architectures: Establish scalable, modular, and efficient architectures for AI agents, LLM-based applications, and generative AI models.
Hands-on AI Development: Implement and optimize generative AI models using frameworks such as OpenAI, LangChain, and RAG.
AI Integration & Deployment: Work with cloud AI platforms (Azure, Google Cloud Platform) to implement best practices for MLOps, model serving, and continuous improvement.
Enterprise AI Strategy: Align AI-driven solutions with business objectives, ensuring scalability, security, and cost effectiveness.
Cross-functional Collaboration: Engage with product teams, data scientists, and engineering teams to ensure seamless integration of AI-powered solutions into business workflows.
AI Governance & Ethics: Establish responsible AI practices, ensuring compliance with data privacy, model bias mitigation, and security best practices.
Evaluation & Optimization: Continuously assess AI agent performance and optimize for improved outcomes.
Hands-on experience in designing and deploying AI-powered agents and multi-agent architectures.
Expertise in Large Language Models (LLMs) such as GPT, BERT, and Llama.
Proficiency in AI frameworks like TensorFlow, PyTorch, and Hugging Face.
Strong knowledge of retrieval augmented generation (RAG) and vector databases (e.g., Vector DBs).
Experience with cloud AI services (Azure Cognitive Services) and containerized deployment using Docker and Kubernetes.
Strong background in API driven development, API and Microservices, and event-driven architectures.
Experience with MLOps, CI/CD Pipeline, and monitoring AI models in production.
Excellent problem-solving, analytical thinking, and effective communication skills.
Experience with AI orchestration/agents frameworks, including AG2, CrewAI, and AutoGPT.
Familiarity with multimodal AI models (text, image, video, audio) and AI personalization techniques.
Knowledge of Responsible AI principles, including bias mitigation and explainability.
Advanced academic background (PhD/Master's) in AI, ML, Data Science, or a related field.
The ideal candidate will possess a strong technical foundation in AI architecture and development, with a focus on delivering innovative solutions that drive business value. A commitment to responsible AI practices and a passion for continuous learning in the rapidly evolving AI landscape are essential.</>