Description and Requirements
Key Responsibilities
AI Solution Design & Development
- Design, develop, and deploy scalable AI applications leveraging Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks.
- Lead the end-to-end lifecycle of AI projects, including requirement analysis, solution architecture, development, testing, deployment, and ongoing optimization.
- Build intelligent AI assistants, AI agents, domain-specific copilots, chatbots, and workflow automation solutions that deliver measurable business value.
- Develop and optimize LLM-powered applications while ensuring performance, reliability, scalability, and security.
Data Engineering & Model Optimization
- Design and maintain robust data pipelines for data collection, transformation, feature engineering, and model training.
- Implement model evaluation frameworks, performance monitoring, prompt engineering strategies, and continuous improvement methodologies.
- Apply best practices for AI governance, responsible AI, model observability, and production deployment.
Software Engineering & Integration
- Write high-quality, maintainable, and production-ready code using Python and modern AI development frameworks.
- Integrate AI capabilities with enterprise systems, APIs, cloud platforms, backend services, and business applications.
- Build scalable microservices and AI-enabled enterprise solutions following software engineering best practices.
Collaboration & Leadership
- Partner with product managers, architects, engineers, and business stakeholders to translate business challenges into AI-driven solutions.
- Provide technical leadership in AI solution design, architecture reviews, and technology selection.
- Mentor junior engineers and foster knowledge sharing across AI, data, and engineering teams.
- Contribute to AI standards, development frameworks, and organizational best practices.
Innovation & Research
- Stay current with advancements in AI, Generative AI, Agentic AI, LLMs, and emerging technologies.
- Evaluate new tools, frameworks, and platforms and provide recommendations for enterprise adoption.
- Drive innovation through experimentation, proof-of-concepts (POCs), and continuous improvement initiatives.
Required Qualifications
- Bachelor's Degree in Engineering, Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related discipline.
- 5+ years of relevant experience in AI/ML, software engineering, data science, or AI solution development.
- Strong programming expertise in Python and experience with modern software development practices.
- Hands-on experience with Generative AI, LLMs, prompt engineering, RAG architectures, AI agents, and Agentic AI frameworks.


