Description

Requirements:

 Bachelor's degree in Computer Science, Engineering, or a related field.

 5+ years of hands-on experience in C#/.NET development.

 2+ years of experience in Machine Learning, Generative AI, or Data Science

projects.

 Strong proficiency in Python for AI/ML development and data processing.

 Experience with Large Language Models (LLMs), GPT models, Transformers,

Hugging Face, and prompt engineering techniques.

 Experience building and integrating AI-powered applications using modern

software engineering practices.

 Solid experience with Azure and/or AWS cloud platforms.

 Knowledge of containerization and orchestration technologies such as Docker

and Kubernetes.

 Experience implementing CI/CD pipelines and DevOps best practices.

 Understanding of AI security, guardrails, responsible AI principles, and data

privacy requirements.

 Strong analytical and problem-solving skills.

 Experience working in Agile and cross-functional environments.

 Excellent communication skills and fluent English.

GOOD TO HAVE

 AI, Cloud, or Data-related certifications.

 Experience delivering production-grade AI solutions.

 Knowledge of MLOps, model monitoring, and AI governance frameworks.

 Experience with Retrieval-Augmented Generation (RAG), Vector Databases, and

AI agents.

 Experience working with enterprise-scale AI platforms and architectures.

Responsibilities:

 Design, develop, and maintain robust C#/.NET applications integrated with AI

and Machine Learning capabilities.

 Build, deploy, monitor, and optimize ML and Generative AI pipelines for

production environments.

 Translate business requirements into scalable software solutions and innovative

AI products, with a focus on NLP and LLM technologies.

 Fine-tune, evaluate, deploy, and optimize pre-trained models for specific

business and product use cases.

 Develop Proofs of Concept (PoCs) and conduct R&D activities to validate

emerging AI technologies.

 Analyze complex datasets and extract actionable insights to support business

objectives.

 Collaborate closely with Product Owners, Data Scientists, Developers, and

business stakeholders to ensure successful delivery.

 Conduct code reviews, ensure software quality, and mentor junior team

members.

 Implement AI governance, security controls, and responsible AI practices across

solutions.

 Maintain comprehensive technical documentation covering software architecture,

AI models, and deployment processes.

 Monitor application and model performance, resolve production issues, and

ensure compliance with SLAs.

 Identify and proactively address technical debt while contributing to continuous

improvement initiatives

Key Skills

Education

Any Graduate