About this role

Design, develop, and deploy Agentic AI, Generative AI, and AI/ML applications using Python and TypeScript.
Build AI-powered assistants, copilots, chatbots, and autonomous AI agents using agentic frameworks, LLMs, and enterprise APIs.
Develop multi-agent and agentic workflows incorporating tool/function calling, planning, memory, reasoning, and autonomous task execution.
Build Retrieval-Augmented Generation (RAG) solutions using vector databases, embeddings, semantic search, and enterprise knowledge sources.
Integrate and orchestrate GPT, Claude, Gemini, Llama, and other foundation models within enterprise applications.
Develop scalable Python and TypeScript/Node.js REST APIs, microservices, and backend services supporting AI and agentic applications.
Implement prompt engineering, structured outputs, function/tool calling, workflow orchestration, and LLM evaluation.
Fine-tune, evaluate, and optimize AI/LLM solutions for accuracy, reliability, latency, scalability, and cost efficiency.
Design AI agent architectures that integrate enterprise tools, APIs, databases, SaaS platforms, and external systems to automate complex business processes.
Implement AI security, privacy, governance, observability, and responsible AI practices across agentic applications.
Optimize application and model performance through caching, asynchronous processing, model selection, token optimization, and scalable cloud architectures.
Collaborate with product managers, solution architects, data scientists, and engineering teams throughout the software development lifecycle.
Develop and maintain production-ready Python and TypeScript codebases, following clean architecture, testing, CI/CD, and software engineering best practices.
Work with distributed/onsite/hybrid engineering teams based in [Location], supporting enterprise AI initiatives and production deployments.

Agentic AI/ Type script / Python

Key skills

About this role