AI Software Engineer  

In this Role, Your Responsibilities Will Be:

Apply diverse AI technologies (frameworks, libraries, models, algorithms) to solve business-specific software challenges

Use Azure OpenAI services and enterprise-grade AI platforms for solution development

Design, train, fine-tune, and integrate machine learning models into production applications

Implement LLM prompt engineering as a core skill for building intelligent solutions

Collaborate with data engineers and scientists to preprocess and analyze data for AI training and testing

Manage data pipelines and engineering tasks to leverage internal business data sources

Develop and deploy AI agents and automation solutions tailored to organizational, functional, and/or departmental activities

Integrate tools via APIs, database connectors, and RPA platforms for seamless workflows

Research, design, and deliver end-to-end AI solutions aligned with organizational goals

Stay current with emerging AI technologies and frameworks

Participate in scrum activities and collaborate with global teams to align technical solutions with business objectives

Utilize agent orchestration frameworks such as but not limited to (Autogen, CrewAI, LangChain Agents, Semantic Kernel) for scalable automation

Maintain and update technical documentation for clarity and scalability

For This Role, You Will Need:

Bachelor’s or Master’s degree or equivalent in Engineering, Computer Science, Artificial Intelligence, IT, or any related field.

Proven background in full-stack development

Strong experience with Python and modern AI/ML frameworks

Hands-on experience incorporating RAG systems and Large Language Models.

Strong analytical and problem-solving skills, with excellent communication and collaboration skills

Preferred Qualifications that Set You Apart:

Minimum of 2 years of experience in AI/ML projects with a solid understanding of AI application design and deployment.

Hands-on experience with Azure, Azure ML Studio, Azure Copilot, and GitHub Copilot for building and managing AI solutions.

Familiarity with AI/LLM frameworks such as Haystack, LangChain, Ollama, or similar technologies.

Strong knowledge of best practices including Agile methodologies, test-driven development (TDD), and DevSecOps principles.

Ability to integrate AI workflows into enterprise environments and leverage cloud-native services for scalability and security.