Job Description

About the Role:

We are seeking a Principal AI Engineer / AI Architect with extensive experience in Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and Agentic AI systems This role requires strategic leadership, architectural design, and delivery of large-scale AI projects You will define technical roadmaps, manage teams, and ensure enterprise-grade AI solutions align with business objectives.

Key Responsibilities:

• Lead and architect enterprise-scale AI solutions leveraging LLMs, multimodal models, and advanced GenAI techniques.
• Design and oversee RAG pipelines and Agentic AI frameworks for complex workflows.
• Define AI architecture standards, scalability strategies, and integration patterns with cloud services.
• Drive effort estimation, resource planning, and delivery timelines for large-scale AI projects.
• Collaborate with senior stakeholders to propose AI-driven solutions and influence technology strategy.
• Ensure compliance with security, governance, and ethical AI principles
• Oversee model deployment, model cost estimation in production environments and ensure robust monitoring.
• Lead MVP development for rapid prototyping and proof-of-concept initiatives.
• Mentor and guide engineering teams, fostering innovation and best practices.

Required Skills:

• Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face).
• Generative AI: Proven experience in LLM fine-tuning, prompt engineering, and production deployment.
• RAG & Agentic AI: Advanced knowledge of embeddings, vector databases (FAISS, Pinecone), and agent orchestration frameworks (LangChain, AutoGen).
• Traditional ML & Deep Learning: Strong foundation in ML algorithms and deep learning architectures (CNNs, RNNs, Transformers).
• Architecture & Leadership: Ability to design scalable AI architectures, manage large teams, and deliver enterprise projects.
• Cloud Expertise: Strong understanding of cloud services (AWS, Azure, GCP), including compute, storage, networking, and AI-specific offerings.
• MVP Development: Experience creating proof-of-concepts and MVPs for rapid prototyping and stakeholder validation.
• Production Deployment: Should have proven capability to production
• Excellent communication and stakeholder management skills.

Preferred Skills:

• Experience with MLOps, CI/CD for AI, and multi-cloud deployments
• Familiarity with cost optimization, security best practices, and disaster recovery strategies
• Exposure to multi-modal AI, agent orchestration, and AI governance frameworks
• Hands-on experience deploying AI models in production environments with monitoring and scaling strategies.
• Cost Estimation: Exposure to estimating LLM model costs prior to deployment, including compute, storage, and inference optimization.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• 12+ years of experience in AI/ML development, with at least 5+ years in Generative AI and advanced AI systems
• Proven track record of leading large-scale AI projects, defining architecture, and managing cross-functional teams.