Senior AI Fullstack Engineer (GenAI & Agentic AI)

Company

hirify.global is hiring for an engineering role focused on production-grade Generative AI and Agentic AI applications.

What you will do

• Design, build, and deploy end-to-end GenAI applications across frontend, backend, LLM integration, enterprise data, and cloud infrastructure.
• Develop RAG pipelines with document ingestion, chunking, embeddings, vector search, reranking, and response generation.
• Build AI agents and agentic workflows with tool calling, orchestration, memory, reasoning patterns, and human-in-the-loop mechanisms.
• Implement LLM evaluation, guardrails, prompt management, context management, caching, session management, observability, and tracing.
• Develop APIs and user interfaces using Python, FastAPI, Node.js, React, Next.js, and TypeScript or JavaScript.
• Deploy and optimize secure, scalable applications on Azure, AWS, or GCP using Docker, Kubernetes or serverless technologies, and CI/CD.

Requirements

• 6+ years of software engineering experience, including strong full-stack application development.
• 2+ years of hands-on experience developing GenAI or LLM-based applications.
• Strong Python, React/Next.js, JavaScript/TypeScript, backend, REST API, and microservices experience.
• Practical knowledge of LLM integration, RAG, embeddings, semantic search, vector databases, prompt engineering, context management, and AI agent frameworks.
• Experience with relational and NoSQL databases such as PostgreSQL, MongoDB, and Redis, plus cloud deployment on Azure, AWS, or GCP.
• Knowledge of Docker, CI/CD, Git, authentication, authorization, API security, data privacy, and secure application development.

Nice to have

• Experience with OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, Llama, multi-agent systems, AI copilots, enterprise search, or conversational AI.
• Experience with LLM-as-a-judge evaluation, human evaluation, feedback loops, fine-tuning, preference data, synthetic data, or MCP/tool integration.
• Knowledge of Kubernetes, Terraform, AI observability, Responsible AI, AI security, governance, and production LLMOps.

Culture & Benefits

• Work closely with product managers, AI/ML engineers, data scientists, architects, and business teams.
• Contribute to code reviews, engineering best practices, and mentoring junior engineers.
• Own solutions through the full lifecycle from prototype and design to production deployment and support.