AI Engineer | Mid
Accountabilities: As an AI Engineer, you will be responsible for designing, developing, and deploying Generative AI solutions that support business transformation and innovation. You will work across the entire AI application lifecycle, ensuring solutions are scalable, secure, observable, and aligned with technical and business objectives.
Design, develop, and deploy Generative AI solutions at scale.
Build robust, secure, and integrated applications connected to enterprise technology ecosystems.
Develop intelligent agents using Large Language Models (LLMs) and frameworks such as LangChain, LangGraph, and LangFlow.
Create AI solutions based on Retrieval-Augmented Generation (RAG), chatbots, intelligent document processing, and classification systems.
Implement agent orchestration workflows and API-based integrations.
Work with cloud AI platforms, including AWS Bedrock (AgentCore), Vertex AI, and Azure OpenAI.
Apply LLMOps practices for the development, deployment, monitoring, and continuous improvement of AI applications.
Define solution architectures and ensure performance, security, scalability, and observability.
Collaborate with multidisciplinary teams to build AI-powered products and business solutions.
Continuously improve AI applications through testing, optimization, and engineering best practices.
Requirements:
The ideal candidate has experience developing Generative AI solutions and strong knowledge of modern AI engineering practices, cloud platforms, and application development.
Bachelor’s degree in Technology-related fields or postgraduate studies in IT.
Professional experience developing Generative AI solutions using cloud services, especially Amazon Bedrock.
Strong knowledge of LangChain and LangGraph frameworks for building intelligent agents.
Experience creating and evolving autonomous agents integrated with Large Language Models (LLMs).
Knowledge of LLMOps principles and the lifecycle management of AI applications.
Experience developing chatbots, classification systems, document processing solutions, and RAG-based applications.
Knowledge of graph modeling using Neo4j and Cypher language.
Experience integrating solutions using MCP (Model Context Protocol).
Understanding of solution architecture, testing strategies, observability, and cloud application optimization.
Experience using Git for version control and collaborative development.
Familiarity with AI-assisted development tools such as AWS Kiro is considered a plus.
Strong analytical thinking, problem-solving skills, and ability to collaborate in multidisciplinary teams.
Passion for emerging technologies and continuous learning.
Benefits:
Fully remote work model.
Opportunity to work with advanced Artificial Intelligence and Generative AI technologies.
Exposure to innovative projects involving LLMs, intelligent agents, and cloud platforms.
Collaborative environment focused on knowledge sharing and professional growth.
Opportunity to contribute to AI-driven digital transformation initiatives.
Work with modern engineering practices, tools, and technologies.
Career development opportunities in a fast-evolving technology landscape.
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?
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