GenAI Developer is a senior software engineer role focused on building AI-powered applications using natural language processing (NLP) and generative AI models. Develop and code in C# or Python, work on prompt engineering and cloud platforms like Azure. Work in an agile environment and collaborate with cross-functional teams.
HOW YOU WILL CONTRIBUTE AND WHAT YOU WILL LEARN
- Design and develop generative AI solutions that align with business goals and optimize performance.
- Collaborate with product managers, data scientists, and designers to create AI-powered applications tailored to customer needs.
- Build and refine natural language processing models, ensuring seamless user interaction through intuitive interfaces.
- Integrate generative AI models into applications and manage end-to-end software life cycles.
- Utilize C# or Python for backend development, focusing on server-side applications and API integrations.
- Stay updated on AI advancements to continuously enhance application performance and capabilities.
- Lead documentation efforts and manage production support issues to ensure system reliability.
- Foster an agile, collaborative environment that encourages innovative problem-solving and creative solutions.
KEY SKILLS AND EXPERIENCE
You have:
- Bachelor's or Master's degree in Computer Science, Engineering, AI, or a related field.
- Overall 5- 9 years of work experience in C# or Python development where natural language processing was a key component.
- Atleast 1 year of experience in developing GenAI applications using prompt engineering, in-context learning etc
- Preferably Certified Cloud Developer (either Microsoft, IBM Cloud, AWS, Google)
- Good understanding of orchestrating frameworks like Semantic Kernel, AutoGen, Langchain, Llamaindex etc.
- Work with an Agile mindset to create value across projects of multiple scopes and scale
It would be nice if you also had:
- 1-2+ years of experience in participating in data and analytics initiatives in a corporate environment or a growing, data-driven startup
- Understanding of advanced analytics, including data management, different types of machine learning approaches and machine learning pipelines
- Understanding of fine tuning large language models
