Staff Software Engineer- Eng

UKG; Pune District; On-site; INR 1,500,000 - 2,000,000; Full time

Job summary

UKG is seeking a skilled Full Stack Engineer in Pune District, Maharashtra. The role focuses on integrating AI-augmented development with technologies like Java, Spring Boot, and Angular. Responsibilities include designing micro frontends and leading technical initiatives.

Candidates should have 7+ years in software development, proficiency in REST APIs, and experience with cloud platforms and modern testing frameworks. This position emphasizes quality and observability in development practices.

Qualifications

• 7+ years of professional software development experience.
• Strong experience in full stack engineering, including microservices architecture.
• Hands-on experience with distributed systems and cloud platforms.

Responsibilities

• Develop and maintain AI-augmented development processes.
• Implement micro frontend architectures.
• Lead and mentor engineering teams.

Skills

AI coding tools

Java

Spring Boot

Angular

TypeScript

Micro Frontend Architecture

REST APIs

GraphQL

Docker

Kubernetes

CI/CD

Education

Bachelor's or Master's degree in Computer Science or Engineering

Tools

Maven

Gradle

Jasmine

Jest

Cypress

SQL Server

PostgreSQL

MongoDB

Redis

Kafka

Job description

Responsibilities

• AI-Augmented Development - Use AI coding tools for development, refactoring, debugging, testing, and documentation. Validate all AI-generated output, own what ships, and model responsible AI‑assisted engineering practices.
• Full Stack Engineering - Build and deliver production‑grade features across the stack using Java, Spring Boot, Angular, and TypeScript, with strong API design, security, scalability, and end‑to‑end ownership.
• Micro Frontend Architecture - Design and implement micro frontend architectures that reduce coupling, support independent deployment, and fit the product's actual needs.
• Agentic Workflow Implementation - Build agentic AI workflows with clear task boundaries, handoffs, and quality gates, and apply them where they add meaningful value.
• LLM Integration - Integrate LLM APIs into product features and internal tools using structured outputs, tool use, and the right mix of prompting, RAG, or fine‑tuning.
• Prompt Engineering & Context Management - Create structured prompts, manage context carefully, improve output quality systematically, and balance reliability with token efficiency.
• Spec-Driven Development - Write clear specifications before coding, use AI to strengthen them, and reduce ambiguity and rework.
• Quality Gates & Engineering Excellence - Maintain high quality standards, validate AI-generated work, and drive strong engineering and testing practices.
• AI-Assisted Code Review - Use AI to strengthen code reviews, identify risks, and provide clear feedback while ensuring compliance with team standards and security expectations.
• AI-Assisted Testing - Build testable software, use AI to improve test coverage and edge‑case detection, and ensure test quality across the stack.
• Service Health & Observability - Build strong observability into services, monitor proactively, and drive root‑cause fixes for production issues.
• DevOps Ownership - Own the full service lifecycle, including delivery, deployment, CI/CD, containerisation, and production operations.
• Leadership & Mentorship - Lead technical decisions, coordinate delivery, mentor engineers, and promote a culture of learning, ownership, and excellence.
• Documentation - Create and maintain clear technical documentation, using AI to accelerate drafting while ensuring human‑reviewed accuracy.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent experience demonstrated through a portfolio of delivered work.
• 7+ years of professional software development experience.
• Java and Spring Boot – RESTful API design, microservices architecture, and Spring Security for production‑grade service security.
• Angular and TypeScript – component architecture, RxJS, state management, and integration with enterprise component libraries.
• Micro Frontend Architecture – practical implementation experience with Module Federation, Single‑SPA, or equivalent MFE patterns.
• REST APIs: mandatory.
• GraphQL: strong advantage.
• OIDC / JWT‑based authentication and authorisation.
• Internal service communication – Service Discovery and routing patterns (e.g., Eureka, Consul, Spring Cloud Gateway).
• Distributed caching – hands‑on experience with at least one of: Redis, Memcached, or Hazelcast.
• Kafka or equivalent event‑streaming platform – producer/consumer patterns and event‑driven architecture fundamentals.
• Relational databases: SQL Server or PostgreSQL – schema design and query optimisation.
• Non‑relational stores: MongoDB – data modelling and aggregation.
• Build tooling: Maven or Gradle.
• Backend testing: JUnit, Mockito, WireMock.
• Frontend testing: Jasmine / Jest and Cypress.
• Docker and Kubernetes.
• CI/CD pipeline ownership.
• Cloud platforms: Azure, AWS, or GCP.
• Observability: Datadog or Prometheus/Grafana – structured logging, distributed tracing, metrics, and alerting.

Additional Qualifications

• Consumer‑driven contract testing – Pact or Spring Cloud Contract.
• Hazelcast distributed computing beyond caching – IMDG and distributed computation patterns.
• Familiarity with vector databases (Pinecone, Weaviate, pgvector) for RAG pipeline implementation.
• Exposure to AI observability – monitoring LLM latency, token consumption, and output quality drift in production.
• Understanding of AI security fundamentals – prompt injection risks and context leakage mitigations.
• Accessibility standards in Angular applications – WCAG compliance and ARIA patterns.
• Commitment to diversity, equity, and inclusion in team building and technical decision‑making.