Artificial Intelligence Engineer

Company Overview

StatusNeo is a Silicon Valley-based company dedicated to creating "Authentic AI" solutions that integrate deeply into business decision-making, development, and operations. Their methodology combines the AuthenticAI™ framework with a Decision Fabric that seamlessly links strategy, data, systems, and execution to produce measurable business impacts. Serving clients globally in sectors such as financial services, telecom, healthcare, travel, retail, and high-tech, StatusNeo offers strategic consulting, product and platform engineering, AI-centric software development lifecycle and DevSecOps, along with managed transformation and operations. Their global presence spans the US, EMEA, and APAC regions, enabling organizations to transition from isolated AI projects to systematic, governed, and outcome-focused AI capabilities. Team members engage in AI-enhanced engineering combined with domain ownership and international teamwork.

Role Summary

This full-time position for an Artificial Intelligence Engineer is based in Gurugram with a hybrid work arrangement balancing onsite and remote work. The role requires designing, developing, and deploying AI models and systems adhering to StatusNeo's AuthenticAI™ and Decision Fabric strategies. Daily tasks involve creating and training models for pattern recognition, natural language processing, and other applications, embedding neural network structures into production-level software, and collaborating with cross-functional teams to translate business challenges into technical implementations.

Key Responsibilities

• Develop, train, and optimize AI models for diverse use cases including NLP and pattern recognition.
• Integrate neural network architectures into scalable production software.
• Collaborate closely with data engineers and product teams to gather requirements and implement technical solutions.
• Apply MLOps best practices, including version control, CI/CD processes, and secure software workflows.
• Contribute to code reviews, documentation, and continuous enhancement of AI engineering procedures.

Required Qualifications

• Strong knowledge of computer science fundamentals such as data structures, algorithms, and object-oriented programming.
• Experience designing, training, and assessing neural networks and deep learning models.
• Proficient in natural language processing techniques including text classification, entity recognition, and language modeling.
• Hands-on experience with AI/ML frameworks and tools like TensorFlow, PyTorch, scikit-learn, Hugging Face, and MLflow or equivalents.
• Practical know-how in deploying AI models to production environments through APIs, microservices, and cloud platforms (AWS, Azure, GCP).
• Familiarity with MLOps, Git-based version control, continuous integration/deployment, and secure software development methodologies.
• Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field, or equivalent practical knowledge.
• Strong communication skills to effectively work within hybrid teams and engage both technical and non-technical stakeholders.
• Proactive ownership of tasks and responsibilities.