AI Forward Developer

INSPYR Global Solutions seeks an AI Forward Developer to work directly with business teams, customers and engineers to turn operational problems into practical AI systems. The full-time role is listed in Hyderabad, Telangana, India, with the job description specifying remote work in India. Compensation is competitive and based on experience.

Responsibilities

• Identify high-value AI use cases with stakeholders and customers; design, prototype and deploy solutions using large language models, machine learning models, APIs and enterprise data.
• Build production-ready applications, workflows, agents, copilots and automation tools, integrating them with enterprise platforms, databases, internal tools and third-party services.
• Collaborate with data, product, security and engineering teams on scalability, reliability and compliance. Iterate based on user feedback; evaluate model performance and improve accuracy, reliability, latency and cost.
• Produce technical documentation, deployment guides and user-enablement materials. Advise stakeholders on AI capabilities, limitations, risks and best practices.

Requirements

• At least 5 years of software engineering experience; Java 11+, Spring Boot, React, TypeScript, REST APIs, strong system design fundamentals and cloud experience, preferably AWS.
• Experience with LLMs, retrieval-augmented generation, AI agents, prompt engineering and AI-assisted development tools such as Cursor, Claude Code or Kiro. The posting also calls for experience with APIs, cloud services, databases and modern development practices, plus hands-on AI/ML work involving technologies such as embeddings, vector databases or agentic workflows.
• A bachelor's degree in computer science, engineering, data science, mathematics or a related field, or equivalent practical experience. Strong problem-solving, communication and stakeholder-management skills; ability to translate non-technical needs into solutions and work independently in ambiguous, customer-facing settings.

Preferred

LangChain, LangGraph, vector databases, AWS-based AI solutions and production AI deployments. Success is measured through production deployments, business impact, user adoption, solution reliability and the conversion of prototypes into reusable platforms or accelerators.