Software Engineer, Senior ( Java , AWS , AI - Ahmedabad )

We are seeking an exceptional developer to join our team at Birst, an Infor Company’s Ahmedabad office, to enhance and sustain our Java-based platform for Business Intelligence and Analytics system. The ideal candidate will have proven experience building and sustaining compelling, interactive web applications with significant exposure to backend design, coding and working knowledge of relational databases.

A Typical Day in the Life Includes:

- Design, build, deploy and maintain scalable cloud-based distributed, multi-tiered, concurrent, cross platforms web applications core infrastructure systems that perform and scale in a multi-tenant cloud environment
- Adding innovative new features in our enterprise class, cloud-scale business intelligence and data analytics products
- Collaborate on UI design with interaction Web designers and backend developers
- Implement RESTful APIs for all new systems and product features
- Drive quality by writing unit, functional, load and performance tests
- Employ solid software engineering practices to ensure high-quality, unit tested, maintainable/extensible code and predictable schedules working in agile environment
- Tracing performance and infrastructure bottlenecks and implementing innovative solutions to resolve them
- Participate in design and code reviews
- Apply AI-assisted development practices to improve engineering productivity while ensuring generated outputs are reviewed, tested, secure, and maintainable.
- Contribute to the design, integration, evaluation, and operational monitoring of AI-enabled product or engineering workflows where applicable.
- Willingness to work across time zones to interact with different stakeholders located across US west coast, Europe and India

Basic Qualifications:

- BE/ME/MCA Computer Science degree
- 4 to 6 years of hard-core software development experience with solid foundation in data structures, algorithms and software design with strong analytical and debugging skills
- Mastery of Java and OO programming
- Expertise in building scalable, concurrent, distributed systems
- Demonstrated expertise with Java 8+, Java Frameworks (Netflix Karyon, DropWizard, Spring Boot), Object-Oriented Design and development principles; and Java Application Servers such as Apache Tomcat; and databases such as SQL Server, MongoDB
- Knowledge of design patterns (GoF, J2EE)
- Demonstrated expertise in software engineering practices (e.g., reading/generating software specs, design patterns, continuous integration)
- Working knowledge of designing, developing and maintaining RESTful based APIs
- Hands on experience with test-driven, agile development practices
- Experience with data architecture and ETL processes and tools
- Experience with Caching, Clustering, Distributed Computing
- Experience building infrastructure/platform for SaaS products is a huge plus
- Hands on experience configuring, using and optimizing systems such as search, caching, messaging, logging or monitoring
- Experience working with open source tools/frameworks such as ActiveMQ, elasticsearch, Jersey, DropWizard, Guice, nginx, tomcat etc. is a big plus
- Good understanding of SQL and relational databases
- Excellent communication and teamwork skills
- A high degree of self-motivation and flexibility with the ability to organize and prioritize multiple tasks

Preferred Qualifications:

- Practical understanding of Generative AI, Large Language Models, prompt engineering, model limitations, and responsible AI usage.
- Hands-on experience using AI-assisted development tools for code generation, debugging, refactoring, unit-test creation, technical documentation, and codebase or architecture understanding.
- Ability to review, test, and validate AI-generated outputs for correctness, security, performance, scalability, and maintainability.
- Ability to evaluate and select suitable AI models based on the use case, output quality, latency, cost, context requirements, privacy, security, and operational constraints.
- Experience creating supervised AI-assisted workflows or agents using prompts, APIs, application context, enterprise data, and tools, with appropriate human approval controls.
- Working knowledge of integrating AI capabilities through APIs or SDKs, including structured outputs, authentication, error handling, retries, timeouts, rate limits, and fallback behavior.
- Understanding of evaluating and monitoring AI-enabled applications, including representative test cases, regression evaluation, logging, tracing, response quality, latency, usage, cost, failures, and human review.
- Understanding of responsible and secure AI practices, including protection of proprietary information, hallucination management, prompt-injection risks, output validation, least-privilege access, auditability, and human oversight.
- Familiarity with Retrieval-Augmented Generation, embeddings, vector search, or other grounding techniques is an added advantage.
- Demonstrated curiosity and willingness to continuously learn, assess, and apply emerging AI technologies to software-engineering problems.