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. We are looking for a Backend Developer with 0–1 years of experience who is eager to build strong backend engineering skills across Java, Spring Boot, APIs, databases, microservices, and AI-powered systems.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.
Key Responsibilities
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
Autonomy & Initiative
- 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
