AI Consultant

About the Role

We are seeking a highly skilled AI Consultant to design, develop, and deploy production-grade AI platforms and intelligent agentic systems. The ideal candidate will have hands-on experience in AI engineering, Retrieval-Augmented Generation (RAG), and cloud-based AI solutions while taking end-to-end ownership of AI product development from architecture through deployment

Key Responsibilities

• Design and deliver production-ready AI platforms, agentic pipelines, and resilient data and retrieval workflows.

• Architect and implement multi-agent systems using LangChain, LangGraph, LlamaIndex, and custom orchestration frameworks where efficiency demands it.

• Build and optimize Retrieval-Augmented Generation (RAG) pipelines across structured and unstructured data sources using vector databases such as ChromaDB, FAISS, Weaviate, and Pinecone.

• Own end-to-end AI feature delivery — retrieval logic, prompt engineering, model selection, API integration, and deployment.

• Build and maintain LLMOps and MLOps tooling, including prompt versioning, evaluation, monitoring, and inference cost optimization.

• Develop full-stack AI applications using Python/FastAPI on the backend and React/Next.js on the frontend.

• Integrate with model providers and platforms including OpenAI, Anthropic, Vertex AI, Azure AI Foundry, Azure OpenAI, and Azure AI Search.

• Design compliance-aware AI systems for regulated industries (e.g., healthcare, pharmaceutical, financial services).

• Take ownership of cloud and infrastructure decisions across AWS (Glue, S3, EMR, EC2), GCP, and edge platforms such as Cloudflare Workers, Vercel, and Netlify.

• Translate ambiguous business requirements into stable, shippable, well-architected systems.

Requirements

• Bachelor's degree in Computer Science or a related discipline.
• 3+ years of experience in AI Engineering, Applied Machine Learning, or Agentic Systems.
• Strong proficiency in Python, FastAPI, LangChain, LangGraph, and LlamaIndex.
• Hands-on experience building production-grade RAG pipelines and multi-agent architectures.
• Experience with vector databases such as ChromaDB, FAISS, Weaviate, and Pinecone.
• Strong understanding of LLMOps, prompt engineering, model evaluation, monitoring, and inference optimization.

• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (Vertex AI).
• Strong full-stack development experience using React/Next.js and backend API development.
• Working knowledge of JavaScript/TypeScript; exposure to Rust, Java, or C/C++ is an advantage.
• Experience designing and deploying scalable AI solutions from concept to production.
• Strong communication, stakeholder management, and problem-solving skills.
• Experience with regulated industries (Healthcare, Pharmaceutical, FinTech), MCP integrations, Chrome Extensions, DevOps/CloudOps, CI/CD, NGINX, Docker/Kubernetes, and serverless platforms (Cloudflare, Vercel, Netlify) is highly desirable.

• Relevant AI, Cloud, or Generative AI certifications will be considered an advantage.