AI Architect

About Us

Netlink is a global technology consulting and digital transformation company that helps organizations leverage emerging technologies to accelerate innovation and business growth. Our expertise spans cloud, data, AI, enterprise applications, and intelligent automation, enabling clients to build scalable, future-ready digital solutions.

We are looking for a passionate Python Developer (AI/ML) who is excited to work on cutting-edge Artificial Intelligence and Generative AI technologies. This role offers an opportunity to build intelligent applications, AI-powered automation solutions, and enterprise-grade AI products while collaborating with cross-functional teams.

Job Description

We are seeking a highly skilled and experienced AI/ML Solution Architect to define and drive the architecture, design, and implementation of AI-powered enterprise solutions.

The ideal candidate will possess deep expertise in Machine Learning, Generative AI, Large Language Models (LLMs), cloud-native AI services, and MLOps practices. You will work closely with business stakeholders, data scientists, engineering teams, and enterprise architects to translate business problems into scalable AI solutions while ensuring security, governance, performance, and operational excellence.

The role requires both strategic thinking and hands-on technical expertise in designing AI platforms, integrating AI capabilities into enterprise applications, and mentoring engineering teams on modern AI architecture best practices.

Key Responsibilities

• Design and define enterprise-wide architecture for Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI solutions.
• Translate business requirements into scalable, secure, and high-performing AI solution architectures.
• Lead the end-to-end solution design covering data ingestion, feature engineering, model development, deployment, monitoring, and continuous improvement. Architect AI platforms that support predictive analytics, NLP, computer vision, recommendation systems, conversational AI, and intelligent automation.
• Evaluate and recommend appropriate AI frameworks, cloud services, vector databases, and development tools.
• Design scalable MLOps pipelines for automated model training, deployment, monitoring, versioning, and governance.
• Build AI architectures leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, AI agents, and enterprise knowledge bases.
• Integrate AI solutions with enterprise applications, APIs, ERP systems, CRM platforms, and cloud-native ecosystems. Establish best practices for AI security, responsible AI, model explainability, governance, compliance, and ethical AI implementation.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, Product Managers, and Business Leaders to deliver AI-driven business solutions.
• Optimize AI model performance, scalability, reliability, and cost efficiency across cloud platforms.
• Evaluate emerging AI technologies and drive adoption of innovative solutions aligned with business objectives.
• Mentor engineering teams on AI architecture, cloud AI services, MLOps, and software engineering best practices. Conduct architecture reviews, proof-of-concepts (POCs), and technology assessments for new AI initiatives.
• Partner with business stakeholders to define AI strategy, roadmap, and enterprise-wide AI adoption.
• Ensure AI solutions adhere to organizational security, privacy, compliance, and regulatory standards.
• Drive continuous innovation by identifying new AI use cases that improve business productivity, operational efficiency, and customer experience. Key Requirements Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.
• 7–12 years of experience in software engineering, data engineering, AI/ML solution development, or enterprise architecture. Minimum 3–5 years of experience architecting enterprise AI/ML solutions.
• Strong experience designing production-grade Machine Learning and Deep Learning applications.
• Hands-on expertise with Generative AI, LLMs, Retrieval-Augmented Generation (RAG), AI Agents, and Prompt Engineering.
• Experience working with Azure AI, AWS AI/ML, or Google Cloud AI services. Strong understanding of enterprise integration patterns, APIs, microservices, and cloud-native architectures.
• Experience implementing scalable MLOps pipelines and model lifecycle management. Knowledge of responsible AI principles, model governance, security, and compliance frameworks.
• Excellent stakeholder management, communication, and presentation skills.
• Proven ability to lead technical teams and mentor engineers across AI and software development disciplines.
• Strong analytical and problem-solving capabilities with a passion for innovation.