Lead Full Stack Engineer

Qualifications - External

• 10+ years of experience in software engineering, AI/ML engineering, or full-stack application development.
• Strong background in AI/ML engineering and enterprise AI solution delivery.
• Proven experience developing full-stack applications using React, Next.js, TypeScript, Node.js, and modern frontend frameworks.
• Experience building production-grade AI applications integrating:
• Machine Learning Models
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Agentic AI Workflows
• Semantic Search
• Proficiency in Python and backend frameworks such as FastAPI, Flask, or Django.
• Experience designing APIs, microservices, BFF architectures, and distributed systems.
• Strong understanding of AI Development Lifecycle (AIDLC), software development lifecycle, and production engineering practices.
• Experience implementing MLOps, LLMOps, CI/CD, monitoring, and deployment automation.
• Cloud-native development experience on Azure, AWS, or GCP.
• Strong understanding of application security, observability, reliability, and performance optimization.
• Proven ability to lead engineering initiatives and collaborate with cross-functional teams.

Preferred Qualifications

• Experience developing enterprise AI copilots, conversational AI applications, and intelligent automation solutions.
• Hands-on experience with LangChain, LangGraph, Semantic Kernel, LlamaIndex, AutoGen, CrewAI, or similar AI frameworks.
• Experience with vector databases and semantic retrieval platforms including Pinecone, Weaviate, ChromaDB, pgvector, Azure AI Search, or equivalent technologies.
• Experience with Databricks, Snowflake, Kafka, Spark, and modern enterprise data platforms.
• Experience building reusable UI platforms, component libraries, and design systems.
• Expertise in frontend performance optimization, accessibility standards (WCAG), SSR/ISR patterns, and responsive design.
• Experience developing event-driven and real-time applications.
• Familiarity with Kubernetes, Docker, Infrastructure-as-Code, and cloud-native deployment practices.
• Experience leading technical design reviews, mentoring engineers, and driving enterprise engineering standards.

Builder Responsibilities:
Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making.