Senior Agentic AI Engineer (Python / TypeScript / Java)

TalentOla View all jobs

Columbus, OH, United States

25 days ago

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Role details

Contract type

Temporary to permanent

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Unit Testing Cloud Engineering Software Design Patterns Memory Management Python (Programming Language) Node.Js Systems Development Life Cycle Software Engineering TypeScript

+13 more

Workflow Management Systems Flask (Web Framework) Large Language Models Multi-Agent Systems Prompt Engineering Generative AI Backend Fastapi Kubernetes Virtual Agents NestJS Restful APIs Microservices

Requirements

12+ years of software engineering experience with strong expertise in Python, TypeScript, or Java.
Candidate should be owning end-to-end delivery with minimal supervision.
Extensive experience building AI applications using Python (FastAPI, Flask, LangChain/LlamaIndex) and TypeScript (Node.js, NestJS, Express) for backend services, AI agents, and orchestration layers.
Strong expertise in Agentic AI architecture, including agent design patterns, multi-agent systems, planning, reasoning, memory management, tool/function calling, and workflow orchestration.
Hands-on experience with orchestration frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK, or similar enterprise AI frameworks
Hands-on experience designing and implementing Agentic AI solutions, autonomous workflows, and enterprise AI applications.
Experience building Retrieval-Augmented Generation (RAG), vector database integrations, tool calling, function calling, and LLM-based applications.
Ability to independently own user stories from requirement analysis through development, unit testing, peer reviews, Dev/UAT testing, deployment, and production support.
Experience developing scalable APIs, microservices, and cloud-native AI solutions on AWS.
Strong understanding of prompt engineering, AI governance, observability, evaluation frameworks, and model optimization.
Collaborate with Product Owners, Architects, Data Scientists, and Platform teams to deliver enterprise AI capabilities.
Mentor engineering teams and drive engineering excellence across the complete SDLC.