AI Solutions Software Developer

As an AI Solutions Software Developer, you will be responsible for designing, developing, testing, and deploying high-performance software systems that integrate advanced artificial intelligence and machine learning technologies. You will collaborate closely with cross-functional teams including data scientists, AI researchers, product managers, and UX designers to translate business requirements into scalable, reliable AI-driven solutions. Your work will directly contribute to the development of innovative products that solve complex problems across various domains (e.g., healthcare, finance, e-commerce, enterprise services).

Key Responsibilities:

• Design and implement software architectures for AI solutions, including data pipelines, model integration, inference engines, and user-facing interfaces.
• Develop and optimize code for machine learning models (e.g., training, validation, deployment) using programming languages and frameworks relevant to AI development.
• Collaborate with data scientists to integrate pre-trained or custom ML models into production-ready software systems, ensuring compatibility, efficiency, and scalability.
• Build and maintain data processing pipelines to handle large volumes of structured and unstructured data (e.g., data collection, cleaning, transformation, storage) that fuel AI models.
• Conduct unit testing, integration testing, and performance testing to ensure the reliability, robustness, and efficiency of AI software solutions.
• Deploy AI solutions to cloud platforms (e.g., AWS, Azure, GCP) or on-premises environments, implementing CI/CD pipelines for seamless updates and maintenance.
• Troubleshoot and resolve technical issues in AI software systems, including model performance bottlenecks, data quality problems, and integration errors.
• Stay updated with the latest advancements in AI/ML technologies, software development practices, and industry trends to continuously improve solution performance and functionality.
• Document software designs, development processes, deployment procedures, and user guides to ensure knowledge sharing and operational clarity.
• Collaborate with product managers to align software development with business goals, prioritize features, and deliver solutions within project timelines.

Qualifications

Required Qualifications:

• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field (Master’s degree preferred).
• 3+ years of hands-on software development experience, with at least 1-2 years focused on AI/ML solution development.
• Proficiency in programming languages commonly used in AI development: Python (required), Java, C++, or JavaScript.
• Strong experience with AI/ML frameworks and libraries
• Knowledge of data processing and storage technologies: SQL (PostgreSQL, MySQL).
• Familiarity with cloud computing platforms (AWS, Azure, GCP) and their AI/ML services (e.g., AWS SageMaker, Azure ML, GCP AI Platform).
• Understanding of software development best practices: Agile/Scrum methodologies, version control (Git), CI/CD pipelines (Jenkins, GitHub Actions), and test-driven development (TDD).
• Experience in designing and implementing scalable, high-performance software architectures for data-intensive or AI-driven applications.
• Strong problem-solving skills, analytical thinking, and the ability to work independently and in cross-functional teams.
• Excellent communication skills (verbal and written) to convey technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications:

• Experience with large language models (LLMs) such as GPT, BERT, or Llama, and their fine-tuning, deployment, and integration into applications.
• Knowledge of MLOps practices, including model versioning, experiment tracking (MLflow, Weights & Biases), and model monitoring in production.
• Familiarity with containerization and orchestration tools: Docker, Kubernetes.
• Experience in a specific industry domain (e.g., healthcare, finance, e-commerce) with AI solution deployment.
• Contributions to open-source AI/ML projects or a strong portfolio of AI software development projects.
• Knowledge of edge AI deployment (deploying AI models on edge devices such as IoT sensors, mobile devices).
• Understanding of data privacy and security regulations relevant to AI solutions handling sensitive data.