Artificial Intelligence Engineer

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Artificial Intelligence Engineer

This is an exciting opportunity for an AI professional who wants to work at the forefront of innovation, shaping AI strategy and delivering impactful solutions for global enterprises.

Role Overview:

The Artificial Intelligence Engineer will design, implement, and integrate AI models into SaaS platforms, enabling automation, decision support, and customer engagement. You will collaborate with cross-functional teams to build scalable, cloud-native systems while ensuring responsible and ethical AI practices.

Key Responsibilities:

• Lead and contribute to AI R&D initiatives that transform enterprise SaaS through intelligent, adaptive systems.
• Design and deploy NLP chatbots, recommendation systems, and predictive analytics engines.
• Develop scalable ML models for automation, anomaly detection, sales forecasting, and customer support optimization.
• Collaborate with product and engineering teams to embed AI into SaaS platform architecture.
• Integrate AI models into cloud-native, microservices-based systems using APIs and data pipelines.
• Research AI/automation trends and contribute to innovation strategies.
• Document architectures and mentor junior engineers to accelerate AI adoption.

Required Skills & Qualifications:

• 2+ years of experience applying AI/ML to enterprise-grade solutions.
• Proficiency in Python, TensorFlow/PyTorch, and NLP frameworks (spaCy, Hugging Face, or similar).
• Experience building chatbots, recommendation engines, or predictive ML models.
• 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.

Preferred Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• Experience with SaaS, CRM, ERP, or workflow platforms.
• Knowledge of vector databases (pgvector, Pinecone) for embedding-based search.
• Exposure to cloud platforms (AWS, GCP, Azure) and MLOps practices.
• Experience in applied AI research or early-stage product development.