Senior AI Engineer

Good co India; United Arab Emirates; On-site; AED 350,000 - 700,000; Full time

Job summary

Good co India is seeking an experienced AI/ML expert to design, develop and deploy advanced AI solutions for complex business challenges in the UAE. You will build Generative AI apps, LLMs, and AI-powered systems, and implement Retrieval-Augmented Generation pipelines and AI agents.

You will research new AI technologies, train and fine-tune models for production, and collaborate with cross-functional teams to deliver scalable, secure solutions with a strong focus on responsible AI practices.

Qualifications

• 6 to 11 years of experience in Software Engineering, AI, ML, or related fields.
• Strong hands-on Python expertise and ML/DL algorithm knowledge.
• Proven experience deploying production-grade AI/ML models.
• Solid understanding of Generative AI, LLMs, RAG architectures, and AI agents.
• Experience with PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
• Familiarity with vector databases and cloud-native architectures.

Responsibilities

• Design, develop, and deploy advanced AI/ML solutions for complex business challenges.
• Build and optimize Generative AI apps, LLMs, and AI-powered systems.
• Develop and implement Retrieval-Augmented Generation pipelines and AI agents.
• Research and apply emerging AI frameworks, algorithms, and architectures.
• Train, fine-tune, and optimize ML/DL models for production environments.
• Develop NLP, computer vision, predictive analytics, and recommendation solutions.
• Create scalable AI architectures and expose models via APIs and microservices.
• Implement prompt engineering, model evaluation, and inference optimization.
• Work with vector databases and knowledge retrieval systems for performance gains.
• Develop and maintain end-to-end MLOps pipelines for training, deployment, monitoring, and improvement.
• Collaborate with engineers, data scientists, product managers, and stakeholders to deliver AI solutions.
• Ensure AI systems meet performance, scalability, security, and privacy requirements.
• Monitor model performance, mitigate bias, reduce hallucinations, and promote responsible AI.
• Optimize AI infrastructure, resources, latency, and deployment costs.
• Mentor junior engineers and contribute to architecture and best practices.

Skills

Python

Machine learning algorithms

Deep learning

NLP

Computer vision

REST APIs

MLOps

Docker

Kubernetes

Cloud platforms (AWS/Azure/GCP)

LangChain

PyTorch

TensorFlow

Scikit-learn

Hugging Face

LlamaIndex

Vector databases (Pinecone/Weaviate/FA

Education

Bachelor's degree in Computer Science / AI / Data Science

Master's degree preferred

PhD helpful

Tools

PyTorch

TensorFlow

LangChain

LlamaIndex

HuggingFace

Pinecone

Weaviate

FAISS

ChromaDB

Docker

Kubernetes

AWS

Azure

GCP

REST API development

Job description

Role & responsibilities

• Design, develop, and deploy advanced AI and machine learning solutions to address complex business challenges.
• Build and optimize Generative AI applications, Large Language Models (LLMs), and AI-powered intelligent systems.
• Develop and implement Retrieval-Augmented Generation (RAG) pipelines, AI agents, and autonomous workflows.
• Research, evaluate, and implement emerging AI technologies, frameworks, algorithms, and architectures.
• Design, train, fine-tune, and optimize machine learning and deep learning models for production environments.
• Develop NLP, computer vision, predictive analytics, and recommendation system solutions.
• Build scalable AI architectures and integrate AI models into enterprise applications through APIs and microservices.
• Implement prompt engineering, model evaluation, fine-tuning, and inference optimization techniques.
• Work with vector databases, embedding models, and knowledge retrieval systems to enhance AI application performance.
• Develop and maintain end-to-end MLOps pipelines for model training, deployment, monitoring, and continuous improvement.
• Collaborate with software engineers, data scientists, product managers, and business stakeholders to deliver AI-driven solutions.
• Ensure AI solutions meet performance, scalability, reliability, security, and data privacy requirements.
• Monitor model performance, identify bias, reduce hallucinations, and implement responsible AI practices.
• Optimize AI infrastructure, computational resources, model latency, and deployment costs.
• Mentor junior AI/ML engineers, conduct code reviews, and contribute to technical architecture and engineering best practices.

Preferred candidate profile

• 6 to 11 years of experience in Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or related technical domains.
• Strong hands-on expertise in Python, machine learning algorithms, deep learning, and statistical modelling.
• Proven experience developing, training, fine-tuning, and deploying production-grade AI/ML models.
• Strong understanding of Generative AI, LLMs, prompt engineering, RAG architectures, and AI agent development.
• Experience with frameworks and libraries such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, and LlamaIndex.
• Hands-on experience with vector databases such as Pinecone, Weaviate, FAISS, or ChromaDB.
• Strong knowledge of NLP, computer vision, neural networks, and model optimization techniques.
• Experience building scalable AI applications, REST APIs, microservices, and cloud-native solutions.
• Familiarity with MLOps, model deployment, monitoring, Docker, Kubernetes, and CI/CD pipelines.
• Experience working with cloud AI platforms and services across AWS, Microsoft Azure, or Google Cloud Platform.
• Strong understanding of data engineering, SQL, NoSQL, data preprocessing, feature engineering, and distributed computing.
• Knowledge of AI model evaluation, explainability, responsible AI, data security, and privacy standards.
• Ability to translate complex business requirements into practical AI solutions with measurable business outcomes.
• Strong analytical thinking, problem-solving, communication, and cross-functional collaboration skills.
• Experience mentoring engineers and contributing to technical architecture and AI engineering standards.
• Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field; master's degree or PhD preferred.
• Relevant certifications and demonstrated AI project experience, research contributions, or technical publications are advantageous.