Job
Description
Role Overview: As an Artificial Intelligence Engineer at our company, you will be responsible for designing, implementing, and integrating AI models into SaaS platforms. Your main focus will be on enabling automation, decision support, and customer engagement by collaborating with cross-functional teams to build scalable, cloud-native systems. It is essential to ensure responsible and ethical AI practices in all your endeavors. Key Responsibilities: - Lead and contribute to AI R&D initiatives aimed at transforming enterprise SaaS through intelligent, adaptive systems. - Design and deploy NLP chatbots, recommendation systems, and predictive analytics engines to enhance user experience. - Develop scalable ML models for automation, anomaly detection, sales forecasting, and optimizing customer support processes. - Collaborate closely with product and engineering teams to seamlessly embed AI into the architecture of SaaS platforms. - Integrate AI models into cloud-native, microservices-based systems using APIs and data pipelines for efficient performance. - Stay updated on AI/automation trends and actively contribute to innovation strategies within the organization. - Document architectures effectively and mentor junior engineers to facilitate the rapid adoption of AI technologies. Required Skills & Qualifications: - 2+ years of experience in applying AI/ML to enterprise-grade solutions. - Proficiency in Python, TensorFlow/PyTorch, and NLP frameworks such as spaCy, Hugging Face, or similar. - Demonstrated experience in building chatbots, recommendation engines, or predictive ML models. - Strong knowledge of algorithms, distributed systems, and data pipeline design. - Familiarity with REST API development, NoSQL/RDBMS design, and query optimization. - Understanding of AI ethics, data privacy, and compliance standards. Preferred Skills & Qualifications: - Bachelors or Masters degree in Computer Science, AI/ML, or a related field. - Experience working with SaaS, CRM, ERP, or workflow platforms. - Knowledge of vector databases like pgvector, Pinecone for embedding-based search functionalities. - Exposure to cloud platforms such as AWS, GCP, Azure, and familiarity with MLOps practices. - Prior experience in applied AI research or early-stage product development. (Note: Additional details about the company were not provided in the job description.) Role Overview: As an Artificial Intelligence Engineer at our company, you will be responsible for designing, implementing, and integrating AI models into SaaS platforms. Your main focus will be on enabling automation, decision support, and customer engagement by collaborating with cross-functional teams to build scalable, cloud-native systems. It is essential to ensure responsible and ethical AI practices in all your endeavors. Key Responsibilities: - Lead and contribute to AI R&D initiatives aimed at transforming enterprise SaaS through intelligent, adaptive systems. - Design and deploy NLP chatbots, recommendation systems, and predictive analytics engines to enhance user experience. - Develop scalable ML models for automation, anomaly detection, sales forecasting, and optimizing customer support processes. - Collaborate closely with product and engineering teams to seamlessly embed AI into the architecture of SaaS platforms. - Integrate AI models into cloud-native, microservices-based systems using APIs and data pipelines for efficient performance. - Stay updated on AI/automation trends and actively contribute to innovation strategies within the organization. - Document architectures effectively and mentor junior engineers to facilitate the rapid adoption of AI technologies. Required Skills & Qualifications: - 2+ years of experience in applying AI/ML to enterprise-grade solutions. - Proficiency in Python, TensorFlow/PyTorch, and NLP frameworks such as spaCy, Hugging Face, or similar. - Demonstrated experience in building chatbots, recommendation engines, or predictive ML models. - Strong knowledge of algorithms, distributed systems, and data pipeline design. - Familiarity with REST API development, NoSQL/RDBMS design, and query optimization. - Understanding of AI ethics, data privacy, and compliance standards. Preferred Skills & Qualifications: - Bachelors or Masters degree in Computer Science, AI/ML, or a related field. - Experience working with SaaS, CRM, ERP, or workflow platforms. - Knowledge of vector databases like pgvector, Pinecone for embedding-based search functionalities. - Exposure to cloud platforms such as AWS, GCP, Azure, and familiarity with MLOps practices. - Prior experience in applied AI research or early-stage product development. (Note: Additional details about the company were not provided in the job description.)
