Mphasis

GEN AI Software Engineer

Bangalore Division, KA, IN

10 days ago
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Summary

Java gen AI (Good to have Profiles who have undertaken migration projects from other platform to java & also wok with gen AI)


Job Title Lead Application Developer – Java, Spring Boot, LLMs Integration (Copilot, Gemini, and

Tachyon)


No years of Relevant Experience 8 years of relevant Experience with 3+ years of lead experience


What we are looking for:

a. The candidate should have strong background in Java-based backend systems, excellent

problem-solving skills, and a passion for innovation through AI-assisted development

b. The candidate is good in communication and needs to collaborate with business analysts,

architects, and QA teams to gather requirements and deliver robust solutions.

c. The identified candidate must have hands on experience in Troubleshooting complex

problems and resolve complex technical issues

d. The candidate should have experience in guiding a team of developers through best

practices, code reviews, and technical decisions.

e. Lead application developer must have hands-on, technically strong Lead Application

Developer to drive the development of scalable enterprise applications using Java Spring

Boot and Spring Batch

f. Hands-on experience designing and implementing RESTful APIs and microservices

architectures.

g. Must have strong understanding of SQL, data pipelines, and data-intensive workflows.

h. Must have experience in integrating modern AI tools and Large Language Models (LLMs) such

as GitHub Copilot, Google Gemini, and Tachyon

i. Must have experience in using GitHub Copilot for code generation, refactoring, and

productivity

j. The candidate should have hands on experience in using Google Gemini and Tachyon for

advanced AI-assisted development, automated documentation, code review, and contextual

AI suggestions.

Nice to have:

1. Should have hands on experience in building ETL-style workflows using Spring Batch for

batch processing jobs.

2. Should have experience in building CI/CD pipelines and containerized deployments

(Docker, Kubernetes).

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