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Job title: AI Engineer

Description of the Role and Key Responsibilities:

The AI Engineer – Trainee will be part of a dynamic technology team focused on building, enhancing, and supporting intelligent software solutions for healthcare applications. The trainee will work under the guidance of senior engineers and architects to design, develop, test, and deploy AI-enabled and full-stack applications. Key Responsibilities include: · Assist in developing and maintaining scalable applications using Java or .Net Full Stack, Python, and modern frameworks. · Support implementation of AI/ML models for use cases such as automation, decision support, and data insights. · Develop and consume RESTful APIs and collaborate on microservices-based architectures. · Perform data preparation, feature engineering, and basic model training using structured and unstructured data. · Participate in code reviews, testing activities, debugging, and performance optimization. · Follow secure coding standards, documentation practices, and organizational development guidelines. · Collaborate with cross-functional teams including product, data, AI, and cloud teams to translate business requirements into technical solutions. · Continuously learn emerging AI, cloud, and full-stack technologies relevant to enterprise healthcare systems.


Qualification and Specialization:

Qualification: Master’s Degree (preferred) in Technology, or a related discipline. Specialization / Skill Set: · Programming Languages: Java or .Net, Python · Full Stack Development: Java/.Net Full Stack Development (FSD) · AI & Machine Learning:

o Fundamentals of Machine Learning and Deep Learning o Exposure to NLP, data analytics, or predictive modeling · Web Technologies: REST APIs, basic frontend technologies (HTML, CSS, JavaScript) · Databases: SQL / NoSQL basics · Cloud & DevOps (Exposure preferred): Cloud-native application concepts, CI/CD basics · Strong analytical, problem-solving, and communication skills


Unique Experience from this Role:

· Hands-on exposure to real-world AI and enterprise healthcare systems. · Opportunity to work on AI-integrated full‑stack applications used by global healthcare clients. · Experience with AI/ML lifecycle, from data preparation to model deployment. · Collaboration with experienced professionals in AI Engineering, Full Stack Development, and Cloud platforms. · Exposure to industry best practices including secure development, compliance, and scalable system design. · Practical understanding of how AI solutions create business value in regulated domains like healthcare.


Learning outcomes for the Trainee:

By the end of the traineeship, the trainee will be able to: · Build and enhance full-stack applications using Java/.Net and Python. · Apply AI/ML concepts to solve business and technical problems. · Work confidently with REST APIs, databases, and cloud-enabled environments. · Understand end-to-end software development life cycle (SDLC) in an enterprise setting. · Follow coding standards, documentation methods, and quality assurance practices. · Collaborate effectively in agile teams and communicate technical ideas clearly. · Be industry-ready as an Associate AI Engineer or Full Stack AI Developer.