Location : onsite/remote posting in USA.
Description
As a Full Stack Developer at ThinkDigits, you will play a pivotal role in building the next generation of intelligent applications. You will develop, test, and maintain end-to-end features, working across the entire stack—from crafting seamless user interfaces to architecting scalable backend microservices and integrating agentic workflows.
We are looking for a builder who is comfortable at the intersection of traditional software engineering and modern AI orchestration. You will partake in every aspect of your projects, including LLM integration, agentic design patterns, and RAG pipelines, ensuring our solutions are not just functional but intelligent and results-driven.
Minimum Qualifications
B.S. in Computer Science, Computer Engineering, or a related technical field (or equivalent professional experience).
3 years of software engineering experience specializing in enterprise-grade software.Proven experience building and integrating AI/ML-driven applications or agentic architecture (e.g., tool-calling, multi-step reasoning, and autonomous task orchestration).
Strong proficiency in Java and Python, with a focus on building scalable, testable, and maintainable backend code.
Hands-on experience with modern frontend frameworks (e.g., React, Angular) to create responsive, accessible, and user-friendly interfaces.
3 years of experience implementing cloud-based distributed systems and designing APIs (REST, RPC, GraphQL, etc.).Solid understanding of OOP principles, data structures, algorithms, and software design patterns (GoF).
Strong proficiency in database technologies and CI/CD solutions.Preferred QualificationsExposure to building, testing, and releasing containerized applications on Kubernetes (AWS EKS, GCP GKE, or Azure AKS).Familiarity with Java web frameworks (Spring Boot, ServiceTalk, etc.) and unit testing frameworks (JUnit, Mockito).
Familiarity with distributed computing systems like Airflow, Spark, or Flink.
Basic understanding of JVM internals (Garbage Collection, Memory Allocation) and networking protocols (HTTP/HTTPS, Load Balancing, OSI model).
Experience with AI evaluation, observability, and debugging techniques to ensure model reliability.