AI Engineering - Developer

AI Senior Engineer

Primary Responsibilities

• Design and develop Generative AI solutions using industry-standard frameworks, tools, and best practices
• Implement core components of GenAI applications, including prompt engineering, retrieval systems, and application integration
• Build and optimize RAG (Retrieval Augmented Generation) implementations for enterprise use cases
• Create reusable components and libraries to accelerate GenAI development across projects
• Conduct code reviews and ensure adherence to coding standards and architectural guidelines
• Troubleshoot and resolve technical issues throughout the development lifecycle
• Collaborate with data engineers and MLOps specialists to integrate solutions into production environments
• Document technical implementations, architectures, and development processes
• Participate in technical discussions with clients to gather requirements and provide implementation insights
• Stay current with emerging GenAI technologies and contribute to internal knowledge sharing

Required Qualifications

• 5+ years of software development experience with at least 2+ years focused on AI/ML technologies
• Strong programming skills in languages commonly used for AI development (Python)
• Hands-on experience with GenAI technologies including LLMs, transformer models, and embedding techniques
• Experience with at least one major AI platform or framework (e.g., OpenAI, Hugging Face, Azure OpenAI, AWS Bedrock)
• Knowledge of vector databases and similarity search algorithms for RAG implementations
• Understanding of software development best practices, including version control, testing, and CI/CD
• Experience building APIs and integrating with third-party services and enterprise systems
• Ability to work in an agile development environment with cross-functional teams
• Strong problem-solving skills and attention to detail
• Bachelor's degree in computer science, Engineering, or related technical field

Preferred Skills

• Experience implementing production-grade GenAI applications for enterprise clients
• Knowledge of prompt engineering techniques and optimization for different LLM models
• Familiarity with fine-tuning approaches for language models
• Experience with front-end frameworks for building AI-enabled user interfaces
• Understanding of data privacy and security considerations in AI implementations
• Knowledge of containerization and cloud deployment technologies
• Experience with MLOps tools and practices for AI solution deployment
• Exposure to different GenAI use cases across multiple industries

Success Factors

• Strong technical curiosity and willingness to explore new GenAI capabilities
• Balance between innovation and practical implementation of solutions
• Effective communication of technical concepts to various stakeholders
• Ability to work independently while collaborating effectively with team members
• Commitment to delivering high-quality code and robust solutions
• Adaptability to rapidly evolving GenAI technologies and methodologies