Role Overview
We are seeking a highly skilled AI Engineer to design, develop, deploy, and maintain Artificial Intelligence (AI) and Machine Learning (ML) solutions that drive business innovation and operational efficiency. The successful candidate will work closely with business stakeholders, data scientists, software engineers, and product teams to translate business requirements into scalable AI-powered applications.
This role requires hands-on experience with Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), MLOps, cloud platforms, and software development best practices. The ideal candidate will be passionate about leveraging AI technologies to solve real-world business challenges while ensuring reliability, scalability, security, and compliance.
Key Responsibilities
- Design, develop, test, deploy, and maintain AI and Machine Learning solutions in production environments.
- Build, train, evaluate, and optimize machine learning and deep learning models for various business use cases.
- Develop and implement Generative AI solutions using Large Language Models (LLMs) and foundation models.
- Design and implement Retrieval-Augmented Generation (RAG) architectures, AI assistants, chatbots, and intelligent automation solutions.
- Develop and maintain AI pipelines for data ingestion, model training, inference, monitoring, and continuous improvement.
- Collaborate with data engineers to build scalable data pipelines and ensure high-quality training datasets.
- Integrate AI capabilities into enterprise applications, APIs, and business processes.
- Implement MLOps practices including automated model deployment, monitoring, version control, and lifecycle management.
- Monitor model performance and address issues related to drift, accuracy, bias, and reliability.
- Ensure AI solutions comply with security, privacy, governance, and regulatory requirements.
- Conduct research and evaluation of emerging AI technologies, frameworks, and industry trends.
- Prepare technical documentation, solution designs, and deployment procedures.
- Participate in Agile ceremonies and contribute to continuous improvement initiatives.
- Provide technical guidance and knowledge sharing across engineering and business teams.
Required Skills & Experience
Technical Skills
- Strong proficiency in Python and AI/ML development.
- Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
- Experience working with Generative AI technologies and Large Language Models (LLMs).
- Strong understanding of Prompt Engineering, Fine-Tuning, and Retrieval-Augmented Generation (RAG) techniques.
- Experience with vector databases such as Pinecone, ChromaDB, Weaviate, FAISS, or similar technologies.
- Knowledge of Natural Language Processing (NLP), Deep Learning, Computer Vision, and Predictive Analytics.
- Experience developing and consuming REST APIs and integrating AI solutions into enterprise applications.
- Familiarity with MLOps tools and practices for model deployment, monitoring, and governance.
- Experience with Docker, Kubernetes, CI/CD pipelines, and containerized deployments.
- Knowledge of SQL and NoSQL databases.
- Understanding of software engineering principles, system design, and cloud-native architectures.
Cloud & Platform Experience
- Experience with one or more cloud platforms:
- Microsoft Azure AI Services / Azure OpenAI
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Experience deploying AI solutions in cloud-based environments.
- Familiarity with cloud security, scalability, and performance optimization.
Professional Skills
- Strong analytical and problem-solving abilities.
- Excellent verbal and written communication skills.
- Ability to translate business requirements into technical solutions.
- Strong stakeholder management and collaboration skills.
- Ability to work independently and within cross-functional Agile teams.
Qualifications
- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
- Master's degree in Artificial Intelligence, Machine Learning, Data Science, or a related discipline is advantageous.
- Minimum 3–5 years of experience in AI/ML Engineering, Data Science, or related roles.
- Proven experience delivering AI solutions in enterprise or large-scale environments.
Preferred Qualifications
- Experience with AI Agents and Agentic AI frameworks.
- Knowledge of Responsible AI, AI Governance, Explainable AI, and Ethical AI practices.
- Experience with LangChain, LlamaIndex, Semantic Kernel, AutoGen, or similar frameworks.
- Experience building enterprise AI assistants and intelligent automation solutions.
- Relevant certifications in AI, Machine Learning, Data Science, Azure, AWS, or GCP.
Key Competencies
- Artificial Intelligence & Machine Learning
- Generative AI & Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Natural Language Processing (NLP)
- Deep Learning
- MLOps & Model Lifecycle Management
- Cloud Computing
- Software Development
- Solution Design & Architecture
- Problem Solving & Innovation
- Stakeholder Management
- Agile Delivery
