AI Engineer (GenAI Developer)

Company Overview

[Company Overview not specified]

Job Summary

We are seeking an experienced AI Engineer (GenAI Developer) with a passion for innovation and a strong desire to learn and experiment. As a key member of our team, you will design, develop, and maintain cutting-edge GenAI applications aimed at solving API integration challenges. Your expertise in Python and exposure to Java/C++ will be critical in building cloud-native, microservice-based agentic solutions. Experience in ML engineering or MLOps is a strong plus.

Responsibilities

• Design and implement GenAI applications (agentic and non-agentic) to address API integration and automation challenges.
• Build and orchestrate agentic workflows using frameworks like LangChain, LangGraph, CrewAI, Semantic Kernel, and OpenAI’s Swarm.
• Develop and expose microservices using FastAPI, Quarkus, or Spring Boot for scalable, cloud-native deployment.
• Integrate and optimize Retrieval-Augmented Generation (RAG) pipelines for document intelligence and semantic search using vector databases (e.g., FAISS, ChromaDB, Pinecone, Astra DB).
• Collaborate with cross-functional teams (DevOps, QA, Product, Data Science) to deliver production-grade GenAI solutions.
• Research emerging GenAI technologies and drive innovation.
• Mentor junior developers and contribute to knowledge sharing.
• Implement MLOps practices for model deployment and lifecycle management.
• Troubleshoot and optimize system performance.
• Contribute to CI/CD pipelines and cloud-native architecture for reliable delivery.

Qualifications

• Hands-on experience with GenAI frameworks (e.g., LangChain, LangGraph, CrewAI, Hugging Face, OpenAI APIs).
• Strong proficiency in Python; working knowledge of Java, Kotlin, Spring Boot, or C++ is a plus.
• Experience with vector databases and semantic search.
• Familiarity with cloud-native deployment (e.g., Azure, Docker, Kubernetes).
• Knowledge of microservices architecture, RESTful APIs, and CI/CD pipelines.
• Exposure to MLOps and automation tools.
• Educational qualifications: [specific degrees not specified, likely relevant to software engineering or computer science].

Preferred Skills

• Familiarity with Agile methodologies and practices.

Experience

• No specific years of experience mentioned, but relevant experience is expected in AI engineering, GenAI frameworks, and MLOps.

Environment

• Work setting, location (remote, in-office, hybrid), and any physical or environmental conditions are not specified.

Salary

• Salary is not specified.

Growth Opportunities

• Career advancement opportunities within the company are not detailed.

Benefits

• Benefits offered are not specified.