Urgent Hiring - AI Developer ( Senior Consultant)

We're looking for a Generative AI Full Stack Developer to design, build, and deploy AI-powered applications for enterprise clients. You'll work across the stack from LLM orchestration and RAG pipelines to production-grade frontend and backend systems as part of client delivery teams solving real business problems with GenAI.

Key Responsibilities

• Design and develop end-to-end GenAI applications, including RAG pipelines, agentic workflows, and LLM-powered features
• Build and maintain full-stack applications (frontend + backend + APIs) that integrate with LLM providers and internal enterprise systems
• Implement prompt engineering, fine-tuning, and evaluation frameworks to optimize model performance and output quality
• Architect and manage vector databases and embedding pipelines for semantic search and retrieval
• Integrate GenAI solutions with cloud platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI)
• Collaborate with data engineers, solution architects, and business stakeholders to translate requirements into scalable technical solutions
• Ensure responsible AI practices data privacy, bias mitigation, hallucination control, and guardrails
• Write clean, tested, maintainable code and contribute to CI/CD pipelines
• Support client workshops, POCs, and technical presentations as needed

Required Skills & Experience

• 3–6 years of professional software development experience, with 1–2+ years hands-on with Generative AI / LLM technologies
• Strong proficiency in Python (FastAPI/Flask/Django) and JavaScript/TypeScript (React, Next.js, Node.js)
• Hands-on experience with LLM frameworks: LangChain, LlamaIndex, Semantic Kernel, or similar
• Experience building RAG (Retrieval-Augmented Generation) systems and working with vector databases (Pinecone, Weaviate, FAISS, Azure AI Search, ChromaDB)
• Familiarity with LLM APIs (OpenAI, Azure OpenAI, Anthropic Claude, AWS Bedrock, Google Gemini)
• Experience with prompt engineering, fine-tuning, and model evaluation techniques
• Solid understanding of REST/GraphQL API design and microservices architecture
• Cloud platform experience (Azure, AWS, or GCP) — deployment, containerization (Docker/Kubernetes)
• Working knowledge of SQL/NoSQL databases
• Exposure to agentic frameworks (AutoGen, CrewAI, LangGraph) is a plus
• Understanding of MLOps/LLMOps practices for monitoring and versioning AI models

Nice to Have

• Experience in consulting or client-facing delivery roles
• Certifications: Azure AI Engineer, AWS Certified ML, or similar
• Exposure to enterprise data governance and responsible AI frameworks
• Experience with CI/CD tools (Git, Jenkins, Azure DevOps)

Education

• Bachelor's/Master's in Computer Science, Engineering, or related field