Agentic AI Java Developer
peopleHum — Bengaluru, Karnataka
₹4–7 LPA (HireSetu estimate) · 0–1 yrs exp · Freshers eligible · Full-time · onsite
HireSetu listing reference 34df5e — confirm requirements below, then apply on the employer site.
Quick answer: A 0-1 year backend job on peopleHum's Java stack, onsite in Bengaluru, with a probation period at the start. The AI part of the title is genuinely there in the product, but the first pass of screening lands on Java, OOP and basic Spring Boot.
From peopleHum's job posting
Designation
-
Experience level
0-1 Years
Location
Bengaluru, India - 560102
About peopleHum
peopleHum is a Human Capital Platform built for the next decade. We are on a mission to transform “The Future of Work.” Winner of the 2019 Global CODiE Award, peopleHum is used by organizations around the world.
It is an intuitive, agile, and integrated platform built for a complete multi-generational employee experience, from hiring to performance, engagement, and HRMS, powered by machine learning and automation.
Find out more: https://www.peoplehum.com
Role Overview
peopleHum is an AI-native human capital global platform built on a microservices architecture with event-driven pipelines and deep LLM integrations on the Java stack. This is not a narrow coding role. You will work across the backend stack, collaborate closely with frontend, QA, and product teams, and learn how production-grade enterprise applications are designed, built, deployed, monitored, and improved.
Exposure to Java, Spring Boot, REST APIs, databases, or AI/LLM concepts is preferred. Curiosity about Agentic AI systems, LLM orchestration, RAG pipelines, and autonomous agents will be a strong advantage.
Ownership & Accountability
Take ownership of assigned backend tasks from understanding requirements to delivering working code
Learn to think beyond tickets by understanding how your work impacts the product and users
Write clean, maintainable, and testable code with guidance from senior engineers
Participate in debugging, deployment, monitoring, and fixing issues in your own code
Develop accountability for quality, correctness, and timely delivery
Communication & Collaboration
Communicate clearly with your team about progress, blockers, and technical questions
Collaborate with frontend, QA, product, and design teams to understand requirements and edge cases
Participate actively in sprint discussions, code reviews, and technical discussions
Share learnings, document work where needed, and be open to feedback
Problem-Solving & Critical Thinking
Break down problems into smaller, solvable parts
Understand the business context behind technical tasks
Learn to think about reliability, security, performance, and correctness while building backend systems
Debug issues systematically and ask thoughtful questions when stuck
Growth Mindset & Learning Agility
Stay curious and continuously learn backend engineering best practices
Build familiarity with emerging technologies, especially AI, LLMs, and automation
Be comfortable working in a fast-paced environment with evolving priorities
Learn quickly from code reviews, production issues, and team feedback
Deliver assigned work with increasing independence
Ask smart questions, unblock yourself, and escalate issues when needed
Show initiative in improving code quality, learning new tools, and understanding system design
Balance speed with clean implementation and long-term maintainability
Must have skills
Basic to good understanding of Java and object-oriented programming Exposure to Spring Boot and building RESTful APIs Understanding of backend concepts such as APIs, services, request-response flow, error handling, and logging Basic knowledge of SQL databases such as MariaDB or MySQL Familiarity with data structures, algorithms, and problem-solving fundamentals Understanding of clean code practices and willingness to follow engineering standards Basic awareness of microservices, event-driven systems, or distributed backend architecture Strong interest in AI/LLM-based systems, agentic AI patterns, RAG pipelines, or automation workflows Good communication skills, ownership mindset, and willingness to learn fast
Good to have skills
Exposure to MongoDB, Redis, or Elasticsearch Basic understanding of authentication and authorization concepts Familiarity with tools such as Maven, Git, JUnit, or SonarQube Awareness of observability, monitoring, logging, or alerting tools Understanding of service discovery, secrets management, or distributed system basics Familiarity with vector databases, embeddings, LangChain, or similar AI frameworks Exposure to langchain-core, langchain-community, or langchain-elasticsearch is a plus
Qualifications
Let's take the first step towards joining our team
Text from peopleHum's official job posting, formatted by HireSetu. The employer's own page is the final word on details.
HireSetu's note
Where the bar actually sits
The must-have list closes with a strong interest in LLM systems, agentic patterns and RAG pipelines. Interest, not shipped experience. Everything above it is ordinary backend work: Java and object-oriented programming, Spring Boot, REST APIs, request-response flow, error handling, logging, SQL on MariaDB or MySQL, plus data structures and algorithms.
If you've built one Spring Boot service and can explain what happens between an incoming request and the database write, you're in range. This fits a fresher or someone a year into a first job who wants to move toward AI-adjacent backend work. Watching a LangChain tutorial is the easy half. Writing and debugging a Java service is what the salary is for.
A week on the backend
Expect tickets. You take a backend task, ask enough questions to understand what's actually needed, write code, get it reviewed, then watch it run and fix what breaks. Debugging, deployment and monitoring are named as part of the role, so things failing in production become your problem too.
Around that: sprint discussions, code reviews, and coordination with frontend, QA and product people. It's onsite in Bengaluru. peopleHum describes the platform as AI-native with LLM integrations already in place, so you're joining a codebase that has these systems, not one where you'd design the first agent pipeline from scratch.
Things to pin down on the call
Ask which module and team you'd sit in. peopleHum spans hiring, performance, engagement and HRMS, and the backend problems look different in each. Ask how AI features are divided between backend engineers and whoever owns the model work, and what a junior actually contributes to a RAG or agent pipeline in the first six months.
Two more: which database you'd touch daily, since MariaDB, MySQL, MongoDB, Redis and Elasticsearch all appear in the listing, and how releases, monitoring and on-call are split across the team. Those answers tell you more about what you'd learn in year one than the job title does.
Drafted with AI from peopleHum's job posting and checked by Prashanth Jakkula before publishing. See our Editorial Policy.
How to apply
- Open peopleHum's careers site with the Apply button.
- Follow the application steps on the site and upload your resume.
- Keep the confirmation email or application number for follow-up.
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