Fullstack AI

About the Role:

We are seeking a  AI Engineer / AI Architect with extensive experience in Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and Agentic AI systems. This role requires high technical acumen, architectural design, and delivery of large-scale AI projects. You will influence 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 and be able to implement them from scratch.
• 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 AI & engineering teams, fostering innovation and best practices.

 

Required Skills:

• Programming: Expert-level proficiency in Python and AI/ML libraries (PyTorch, TensorFlow, Hugging Face) and FastAPI.
• Should know the basics of frontend development
• 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.
• Excellent communication and stakeholder management skills.

 

Additional 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.
• 3+ years of experience in AI/ML development, with at least 2+ years in Generative AI and advanced Agentic AI systems.
• Proven track record of implementing large-scale AI projects