[Hiring] Director of AI Engineering @Ardham Technologies

Role Description

The AI Engineer will play a key role in developing Ardham Technologies' artificial intelligence capabilities, focusing on improving internal operations and creating innovative AI solutions for clients. This position will design, develop, deploy, and optimize AI-powered applications, intelligent agents, automation workflows, and machine learning solutions that solve real-world business challenges.

• Work across Ardham's internal departments to identify opportunities for AI to improve efficiency, automate processes, enhance decision-making, and create measurable business value.
• Shape Ardham's broader AI strategy and the development of AI capabilities for clients.
• Hands-on engineering and consulting role requiring strong technical expertise in Generative AI, Large Language Models (LLMs), agentic AI, machine learning, cloud infrastructure, and MLOps.
• Translate business needs into practical technology solutions.
• Influence technologies, standards, architecture, security practices, and service offerings defining the company's AI practice.

Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field.
• 4+ years of professional experience in software engineering, machine learning engineering, AI development, or a closely related discipline.
• Demonstrated experience developing and deploying AI or machine learning applications in production environments.
• Strong programming experience with Python and SQL.
• Hands-on experience working with Generative AI, Large Language Models, and modern AI development frameworks.
• Experience developing cloud-native applications and working with enterprise cloud infrastructure.
• Experience integrating AI solutions with databases, APIs, and existing business applications.
• Strong understanding of software development principles, system architecture, and application performance optimization.

Requirements

• Design, develop, test, and deploy AI and machine learning solutions addressing business and operational challenges.
• Build and implement Generative AI applications using Large Language Models (LLMs) and modern AI development frameworks.
• Develop intelligent AI agents and multi-agent systems for automating complex business processes and workflows.
• Design and implement Retrieval-Augmented Generation (RAG) solutions to improve AI accuracy and access to enterprise knowledge.
• Develop AI-powered applications that integrate with existing enterprise systems, databases, and APIs.
• Evaluate and optimize AI models for performance, scalability, accuracy, and cost efficiency.
• Research emerging AI technologies and recommend practical applications for internal operations and client environments.
• Develop and maintain LLM-powered applications using frameworks such as LangChain, LangGraph, Google ADK, or similar technologies.
• Design agentic AI architectures supporting autonomous task execution, intelligent decision-making, and workflow orchestration.
• Implement semantic search, vector databases, embeddings, and knowledge retrieval systems.
• Build AI solutions capable of interpreting natural-language requests and interacting with structured and unstructured data.
• Integrate AI models with enterprise applications through APIs, Model Context Protocol (MCP), and other integration methods.
• Develop and maintain appropriate controls, validation processes, and monitoring to ensure AI-generated outputs meet business requirements.
• Evaluate emerging AI platforms, frameworks, and development tools for potential adoption.
• Design, train, evaluate, and deploy machine learning models using modern development frameworks.
• Develop and optimize data pipelines supporting AI model training, inference, and analytics.
• Work with structured and unstructured datasets to identify patterns, automate analysis, and support predictive capabilities.
• Implement data preprocessing, feature engineering, and model evaluation techniques.
• Optimize model inference performance, processing efficiency, and resource utilization.
• Collaborate with data engineering and infrastructure teams to ensure reliable access to enterprise data.
• Support the development of scalable AI solutions capable of processing large datasets and complex workloads.
• Collaborate with internal stakeholders and clients to identify opportunities where AI can improve operational efficiency and business outcomes.
• Translate business requirements into practical AI solutions and technical implementation plans.
• Participate in technical discovery sessions, solution design discussions, and project planning activities.
• Develop proof-of-concept applications and demonstrations to validate proposed AI solutions.
• Partner with engineering, managed services, cybersecurity, and project management teams to support successful deployments.
• Communicate technical concepts, project progress, and recommendations to technical and nontechnical audiences.
• Provide technical guidance on AI capabilities, limitations, implementation considerations, and operational requirements.
• Assist with evaluating the business impact and return on investment of AI initiatives.

Company Description