Senior Software Engineer - AI Enabled Backend Systems

peopleHum; Bengaluru; On-site; INR 2,800,000 - 4,200,000; Full time

Job summary

PeopleHum in Bengaluru is seeking a Senior AI Engineer to design and build scalable backend services using Java and Spring Boot, and to advance AI and agentic capabilities within our platform.

This role focuses on integrating LLMs, tool calling, and enterprise data workflows, collaborating with product and AI teams to deliver reliable, production-ready features.

Qualifications

• Bachelor’s degree in Computer Science, IT, Engineering, or related field, or equivalent practical experience.
• Advanced technical qualifications are a plus.
• Hackathon participation, open‑source contributions, AI projects, or engineering accolades are advantages.

Responsibilities

• Design, develop, test, and maintain scalable backend services using Java and Spring Boot.
• Build reliable REST APIs, microservices, and event‑driven backend systems.
• Design backend architectures capable of handling high‑volume enterprise workloads.
• Work with MySQL, MongoDB, Kafka, and other data and messaging technologies.
• Build and integrate Agentic AI workflows into enterprise applications.
• Develop backend services that allow AI agents to securely interact with APIs, enterprise data, workflows, and business systems.
• Integrate applications with Large Language Models and LLM APIs.
• Work on tools such as tool calling, structured outputs, agent orchestration, memory, and multi‑step AI workflows.
• Design guardrails, validation mechanisms, permissions, and fallback workflows for AI features.
• Build APIs and services that connect AI capabilities with existing peopleHum product workflows.
• Evaluate AI outputs for reliability, latency, cost, and production readiness.
• Collaborate with product and engineering teams to translate requirements into scalable solutions.
• Own features end‑to‑end from design to monitoring and improvement.
• Write clean, well‑described code and participate in code reviews and debugging.
• Identify performance bottlenecks and improve scalability and reliability.
• Contribute to CI/CD, observability, monitoring, and production engineering practices.

Skills

Java

Spring Boot

REST APIs

Microservices

Data Structures & Algorithms

OOP & Design Patterns

MySQL

MongoDB

Kafka

Distributed Systems

Git & CI/CD

Testing

Education

Bachelor’s degree in Computer Science or related field

Tools

Docker

Kubernetes

AWS/Azure/GCP

Job description

About PeopleHum

peopleHum is a Human Capital Platform built for the next decade of work. We are on a mission to transform the future of work by helping organizations deliver better employee experiences across hiring, HR, performance, engagement, and workforce management.

About PeopleHum

peopleHum is a Human Capital Platform built for the next decade of work. We are on a mission to transform the future of work by helping organizations deliver better employee experiences across hiring, HR, performance, engagement, and workforce management. Winner of the 2019 SIIA CODiE Award for Best HCM Solution, peopleHum is used by organizations across the world. Our platform combines intuitive workflows, automation, AI, and data to help businesses manage the complete employee journey. Find out more: https://www.peoplehum.com

About The Role

We are looking for a Senior AI Engineer with strong hands‑on experience in Java and Data architecture to join our engineering team.

You will design and build scalable backend services that power the peopleHum platform while also working on the next generation of AI and Agentic AI capabilities within our products.

This role is ideal for an engineer who enjoys solving complex backend problems, building reliable distributed systems, and exploring how AI agents, Large Language Models, tools, workflows, and enterprise data can work together to automate real business processes.

You will work closely with product managers, frontend engineers, AI engineers, and other backend developers to take features from idea to production.

Key Responsibilities

• Design, develop, test, and maintain scalable backend services using Java and Spring Boot.
• Build reliable REST APIs, microservices, and event‑driven backend systems.
• Design backend architectures capable of handling high‑volume enterprise workloads.
• Work with MySQL, MongoDB, Kafka, and other data and messaging technologies.
• Build and integrate Agentic AI workflows into enterprise applications.
• Develop backend services that allow AI agents to securely interact with APIs, enterprise data, workflows, and business systems.
• Integrate applications with Large Language Models and LLM APIs.
• Work on concepts such as tool calling, structured outputs, agent orchestration, retrieval, memory, context management, and multi‑step AI workflows.
• Design guardrails, validation mechanisms, permissions, and fallback workflows for AI‑powered features.
• Build APIs and services that connect AI capabilities with existing peopleHum product workflows.
• Evaluate AI‑generated outputs for reliability, latency, cost, and production readiness.
• Collaborate with product and engineering teams to translate business requirements into scalable technical solutions.
• Own features through the complete engineering lifecycle, including design, development, testing, deployment, monitoring, and continuous improvement.
• Write clean, maintainable, testable, and well‑described code.
• Participate actively in code reviews, technical discussions, debugging, and engineering design sessions.
• Identify performance bottlenecks and improve application scalability and reliability.
• Contribute to CI/CD, observability, monitoring, and production engineering practices.

AI And Agentic AI Skills

Candidates should have practical exposure to or a strong understanding of modern AI application development, including:

• Large Language Models and LLM APIs
• Prompt engineering and structured outputs
• Function calling / tool calling
• AI agents and agentic workflows
• Retrieval‑Augmented Generation (RAG)
• Embeddings and vector search
• Context and conversation management
• Multi‑step AI workflows
• Connecting LLMs with APIs, databases, and enterprise applications
• AI output validation, guardrails, and error handling
• Hands‑on experience building an AI agent, LLM‑powered application, RAG system, AI automation, or production AI feature will be highly valued.

What We Are Looking For

We value engineers who:

• Enjoy solving difficult engineering problems rather than simply implementing tickets.
• Are curious about how Agentic AI can transform enterprise software.
• Can balance experimentation with engineering discipline.
• Think about scalability, reliability, security, and maintainability while building features.
• Take ownership of problems from discovery through production.
• Learn new technologies quickly and apply them practically.
• Communicate clearly and collaborate effectively with engineering and product teams.
• Are comfortable questioning existing approaches and proposing better solutions.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
• Advanced technical qualifications are a plus.
• Hackathon participation, open‑source contributions, AI projects, technical competitions, or engineering accolades are an advantage.

Must have skills

• 2-4 years of professional software development experience.
• Strong hands on programming experience with Java.
• Strong experience with Spring Boot and backend application development.
• Strong understanding of Data Structures and Algorithms.
• Good understanding of Object‑Oriented Programming, design patterns, and system design fundamentals.
• Experience building REST APIs and microservices.
• Hands‑on experience with relational databases such as MySQL.
• Experience working with MongoDB or other NoSQL databases.
• Working knowledge of Kafka or other messaging/event‑streaming systems.
• Understanding of distributed systems, concurrency, caching, and asynchronous processing.
• Experience with Git, CI/CD pipelines, debugging, testing, and software engineering best practices.
• Ability to write production‑quality code with appropriate unit and integration tests.

Good to have skills

• Experience with Agentic AI frameworks or orchestration tools such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
• Exposure to Model Context Protocol (MCP) or similar tool‑integration patterns.
• Experience working with vector databases or vector search.
• Exposure to cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker and containerized applications.
• Understanding of Kubernetes and cloud‑native application development.
• Experience implementing observability for distributed or AI‑powered applications.
• Understanding of authentication, authorization, data privacy, and secure API development.
• Experience working in a SaaS product environment.
• Participation in hackathons, open‑source projects, or AI engineering projects.