Artificial Intelligence Engineer

Job Summary:

AI Solution Designer

Key Responsibilities:

Solution Design & Architecture

• Translate business problems into AI/ML-driven solution designs.
  
• Define scalable AI/ML solution architectures using appropriate models, frameworks, APIs, and data pipelines.
  
• Collaborate with data engineers, ML engineers, and business stakeholders to ensure alignment.
  

Proof of Concept Development

• Design and develop PoCs to validate feasibility, performance, and business value of proposed AI solutions.
  
• Rapidly prototype AI features using tools such as Python, TensorFlow, PyTorch, Hugging Face, OpenAI APIs, LangChain, etc.
  
• Document PoC findings, results, and recommendations for full-scale implementation.
  

Technical Analysis & Documentation

• Conduct deep technical evaluations of AI/ML models, including accuracy, performance, and risk.
  
• Create detailed technical documentation including solution architecture diagrams, data flow diagrams, and API specs.
  
• Present PoC results and technical recommendations to stakeholders and executive teams.
  

Stakeholder Engagement

• Engage with cross-functional teams (Product, IT, Business, and Data teams) to understand needs and gather requirements.
  
• Act as a bridge between data science, engineering, and business teams to ensure successful delivery of AI initiatives.
  

Innovation & Best Practices

• Stay updated with the latest trends in AI, including LLMs, Generative AI, and AutoML.
  
• Recommend tools, frameworks, and platforms that can accelerate PoC and solution delivery.
  
• Promote reusability and modular architecture principles for AI solution components.

• Design, develop, and deploy conversational AI solutions using various tools such as Wren AI, Voice Flow, and ML algorithms.
  
• Collaborate with cross-functional teams to integrate AI models into existing systems and applications.
  
• Develop generative AI models for text generation, image processing, and other forms of data manipulation.
  
• Troubleshoot issues related to AI model performance and optimize system architecture for improved efficiency.
  

Required Skills & Experience:

• Proven experience in designing AI/ML solutions and delivering PoCs in a business context.
  
• Strong programming experience with Python; exposure to ML libraries like Scikit-learn, TensorFlow, PyTorch.
  
• Experience with cloud platforms (AWS, Azure, GCP) and AI services (SageMaker, Azure ML, Vertex AI).
  
• Hands-on with APIs and frameworks like OpenAI, LangChain, FastAPI, Flask.
  
• Familiarity with MLOps tools (MLflow, DVC, Kubeflow) is a plus.
  
• Strong problem-solving, analytical, and architectural thinking abilities.
  
• Excellent communication and stakeholder management skills.
  

Preferred Qualifications:

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
  
• Certifications in AI/ML technologies or cloud platforms.
  
• Experience with enterprise AI systems or AI product development lifecycle.
  
• 3-6 years of experience in Conversational AI development or a related field.
  
• Strong understanding of AIMl, Python programming language, TensorFlow/PyTorch machine learning frameworks.
  
• Experience with natural language processing (NLP) techniques including large language models like BERT.