Senior GenAI Engineer

About the Role

We are seeking a highly skilled and hands-on Senior GenAI Engineer to join our team. The ideal candidate will bring 7–8 years of software engineering experience , with a strong focus on building and implementing Generative AI (GenAI) solutions .

This is a hands-on technical role suited for a self-driven professional who enjoys designing, developing, and deploying innovative AI solutions. You’ll play a key role in delivering production-grade GenAI systems — writing high-quality code, solving complex problems, and bringing our AI vision to life.

You’ll collaborate closely with technical leaders to execute architectural strategies and will have opportunities to influence design decisions through your practical expertise.

Key Responsibilities

Hands-on Development : Contribute directly to the design, development, and deployment of GenAI solutions with clean, scalable, and maintainable code.

Agentic AI Implementation : Build and implement autonomous AI agents using frameworks such as LangChain and LangGraph , creating sophisticated multi-step workflows with robust state management and tool integration.

• .NET and Python Integration : Develop and maintain seamless integrations between Python-based GenAI models and the .NET technology stack , leveraging APIs and microservices.

Copilot and AI Tooling : Effectively use GitHub Copilot and other AI-assisted development tools to enhance productivity and streamline development processes.

LLM / SLM Integration : Work with Large and Small Language Models , designing intelligent routing strategies to optimize performance and cost efficiency.

Engineering Best Practices : Apply solid engineering principles—unit testing, integration testing, and code reviews—to maintain high standards of code quality and reliability.

Continuous Learning : Stay current with GenAI advancements, adopting emerging frameworks and technologies to drive innovation.

Required Skills & Qualifications

7–8 years of professional software engineering experience, including 3–4 years focused on GenAI development .

Proficiency in Python and experience with major GenAI frameworks such as PyTorch, TensorFlow, or Hugging Face .

Strong expertise in .NET (C#, ASP.NET Core) and adherence to engineering best practices (SOLID, clean code principles).

Proven hands-on experience with LangChain and LangGraph , demonstrating real-world implementation of agentic workflows.

Experience in LLM / SLM integration , with understanding of RAG (Retrieval-Augmented Generation) and model distillation .

Practical experience leveraging GitHub Copilot or similar tools in a professional setting.

Strong understanding of cloud-native architecture , microservices , and containerization (Docker, Kubernetes) on Azure, AWS, or GCP .

Excellent problem-solving skills, strong ownership mindset, and ability to thrive in a fast-paced, evolving GenAI landscape.

Preferred Qualifications

Bachelor’s or Master’s degree in Computer Science , Engineering , or related field.

Experience with GenAIOps practices for monitoring and maintaining AI systems in production.

Background in data science —including data preparation, feature engineering, or predictive modeling.

Familiarity with distributed systems , API design , and performance optimization techniques.