Model N, Inc. is looking for a junior developer for its Life Science platform. The candidate should be hands-on with Java and related technologies, with a willingness to learn modern backend patterns, including AI-enhanced features.

n Job Responsibilities Develop features and code to specified requirements

Identify and reuse existing components or define new reusable components

Prioritize work assignments and deliver on schedule

Write JUnit tests with adequate code coverage

Participate in performance tuning when required

Build and maintain RESTful APIs following platform standards Job Qualification

2-4 years of relevant software development experience

Robust object-oriented design and Java programming skills

Enterprise application development experience with J2EE application servers, preferably WebLogic or JBoss

Experience with Oracle, SQL required; Performance tuning is a plus

Good understanding of browser and servlet-based application structure

Excellent communication and interpersonal skills

Experience with Unix or Linux preferred

Experience with Agile methodologies a plus

Knowledge of Web API Development using REST / GraphQL is a plus

Knowledge of SSO implementation using SAML/OpenID protocols is a plus

Knowledge of CI/CD, containerization, and Orchestration technologies is a plus





Willingness to work on any technology

Fast learner, able to pick up new ideas and approaches quickly

BE / BTech in Computer Science, or equivalent

AI & LLM Skills (Preferred)

Willingness to learn and implement features powered by AI-driven insights and recommendations

Understanding of LLM (Large Language Model) concepts and their integration into backend systems—including API consumption, prompt optimization, and result handling for server-side operations.

Familiarity with implementing intelligent business logic: recommendation engines, predictive analytics, auto-categorization of features/workflows, and smart defaults based on LLM analysis

Understanding of data governance and privacy requirements for AI systems—PII handling, audit logging, data retention policies, and compliance with healthcare/life science regulations.

Knowledge of monitoring and observability for AI-enhanced backends—tracking LLM API costs, inference latency, model performance degradation, and business impact metrics.

Familiarity with fine-tuning or prompt engineering at the backend level to optimize LLM outputs for specific use cases and to enable A/B testing of AI features. n

📌 Member Technical Staff (Java, SQL, Platform Development) (Hyderabad)
🏢 Model N
📍 Hyderabad