Artificial Intelligence Engineer

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Job Summary:

We are seeking a skilled and innovative AI Engineer with expertise in generative and agentic AI solutions, has exposure to deep learning, machine learning, and should be well versed in Python, PHP and Node.js. Exposure to AWS technologies would be an add-on. The ideal candidate will play a key role in designing, developing, and deploying intelligent AI systems, with a focus on natural language interfaces and large-scale generative models.

Key Responsibilities:

• Develop and deliver AI MVPs to test concepts, gather feedback, and accelerate product innovation cycles. These can range from testing to production-grade models using various technologies available at our disposal.
• Develop agentic AI solutions capable of reasoning, autonomous decision-making, and multi-step task execution.
• Have an understanding of the security risks and end-to-end project development lifecycle for AI solutions
• Leverage AWS services (e.g., SageMaker, Lambda, EC2, S3) for AI model training, deployment, and scaling.
• Work with generative AI models (e.g., GPT, DALL•E, Stable Diffusion) to develop creative and automated solutions.
• Build, train, and optimise machine learning and deep learning models for various use cases.
• Integrate AI models with backend systems and databases using Python and SQL.
• Conduct data preprocessing, feature engineering, and model evaluation.
• Collaborate cross-functionally with product, engineering, and data teams to deliver AI-powered features.
• Research and implement cutting-edge techniques in LLMs, autonomous agents, and generative AI. Ensure scalability, reliability, and performance of deployed AI models.
• Maintain documentation and version control of the AI model development lifecycle.

Required Skills & Qualifications:

• Strong programming skills in Python and familiarity with AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Understanding of the PHP language would be an add-on.
• Open to learning new technologies as per the project-based requirements.
• Proven experience with chatbot development, even with no-code platforms.
• Hands-on experience with generative AI models (OpenAI, Hugging Face Transformers, or similar).
• Proficiency in SQL and relational databases.
• Practical knowledge of AWS cloud services, including SageMaker, Lambda, S3, EC2, and API Gateway.
• Understanding of machine learning and deep learning concepts and algorithms.
• Familiarity with building or fine-tuning LLMs and experimenting with autonomous agent frameworks.
• Open for Mid-level candidates who may not have led full-scale production deployments of agentic AI yet, but must have POC/MVP delivery experience.
• Familiarity with NLP techniques such as sentiment analysis, text summarisation, and intent recognition.
• Strong problem-solving and analytical thinking skills.
• Excellent communication and teamwork abilities.

Preferred Qualifications:

• Experience with agentic AI frameworks and autonomous AI agents for multi-step workflows and reasoning tasks.
• Background in LLM fine-tuning, reinforcement learning with human feedback (RLHF), and prompt engineering.
• Experience with cloud platforms (AWS, GCP, Vertex AI) and deploying models in production.
• Knowledge of MLOps practices and tools (e.g., MLflow, Docker, CI/CD pipelines).
• Familiarity with

  security, compliance, and governance

  for cloud AI systems.
• Experience scaling MVPs to enterprise-grade AI solutions.
• Prior experience in deploying and scaling AI solutions in real-world environments.

Education:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Experience:

• Ideally,2-8 years in software engineering, data science, or AI/ML-focused roles specifically in LLMs, generative AI, agentic solutions, or chatbot development.