Lead Engineer - Target India

Target; Bengaluru; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Target in Bengaluru, India seeks a Lead Engineer to provide technical leadership and architectural direction while remaining hands-on in building scalable, production-grade systems. You will shape engineering standards, drive modernization, and enable AI-powered capabilities across the platform.

You will evaluate technologies, design secure, high-performance architectures, and govern services with strong emphasis on observability and reliability.

Qualifications

• Advanced proficiency in Java and backend systems.
• Strong experience with microservices architectures and distributed systems.
• Expertise with Spring Boot or Micronaut and reactive programming models.
• Hands-on experience with AI/LLM integration in applications.
• Experience with messaging systems such as Kafka or RabbitMQ.
• Proficiency with NoSQL (Cassandra, MongoDB) and SQL (PostgreSQL).
• Experience building and managing CI/CD pipelines (Jenkins, GitLab).
• Strong unit and integration testing skills (JUnit, Spock, TestContainers).
• Experience with Cloud Platforms (AWS, GCP, Azure).
• Expertise in containerization and orchestration (Docker, Kubernetes).
• Strong monitoring/observability skills (Grafana, ELK, Prometheus).
• Solid understanding of Event-Driven Architecture.

Responsibilities

• Provide technical leadership and architectural direction.
• Lead evolution of engineering standards and best practices.
• Hands-on development on complex, high-impact components.
• Drive AI/LLM integration across core applications.
• Ensure observability, reliability, and scalable deployments.
• Champion reusable components and enterprise-wide architectural patterns.
• Guide data governance and platform optimization initiatives.

Skills

Java

Microservices

Spring Boot

AI integration

Messaging Systems

Databases

CI/CD

Testing

Cloud Platforms

Containerization

Monitoring

Event‑Driven Architecture

Tools

Docker

Kubernetes

Jenkins

GitLab

Kafka

RabbitMQ

PostgreSQL

MongoDB

Cassandra

Grafana

Prometheus

ELK

Job description

Lead Engineer – Role & Responsibilities

As a Lead Engineer, you will provide technical leadership and architectural direction while remaining hands-on in building scalable, resilient, and production-grade systems. You will play a critical role in shaping engineering standards, driving modernization, and enabling intelligent, AI-powered capabilities across the platform.

Key Responsibilities

• Technology Evaluation & Innovation
  • Evaluate emerging technologies and contribute to architectural decision-making, considering alignment with Target's technical ecosystem, long-term maintainability, scalability, and total cost of ownership.
  • Lead research initiatives and proof-of-concept efforts to validate new tools, frameworks, and platforms before adoption.
• Architecture & Engineering Excellence
  • Design and own scalable, secure, high-performance architectures.
  • Establish and evolve engineering standards and best practices in complex or ambiguous environments.
  • Lead service design, lifecycle management, and overall technical governance of team-owned platforms.
  • Ensure code quality, infrastructure standards, and long-term sustainability of services.
• Hands-On Development & Delivery
  • Contribute directly to development efforts, particularly on complex and high-impact components.
  • Ensure solutions are production-ready, deployable, resilient, and scalable.
  • Drive implementation quality through strong testing, automation, and CI/CD practices.
• Enterprise Impact & Thought Leadership
  • Provide technical thought leadership to promote reusable components and consistent architectural patterns.
  • Participate in planning and designing services with enterprise-wide impact.
  • Guide the team in resolving routine and moderately complex technical challenges, escalating risks when necessary.
• Observability & Reliability Engineering
  • Champion a culture of observability and operational excellence.
  • Ensure monitoring, logging, and metrics are embedded into services.
  • Leverage operational data to continuously improve system stability, performance, and reliability.
  • Align monitoring strategies with organizational observability principles.
• AI & Intelligent Systems Integration
  • Integrate Large Language Models (LLMs) and Generative AI capabilities into core applications.
  • Design and implement safeguards to mitigate hallucinations and improve AI reliability.
  • Build and scale agentic frameworks and AI-driven automation solutions to enhance business processes.
• Data Governance & Platform Optimization
  • Influence and evolve data standards, policies, and governance practices.
  • Configure, optimize, and monitor data management platforms with minimal oversight.
  • Identify performance and efficiency improvements across data systems.

Required Skills & Expertise

• Advanced proficiency in Java , including backend systems and automation workflows
• Strong experience in Microservices Architecture and distributed systems
• Expertise with Spring Boot or Micronaut , including reactive programming models
• Hands-on experience with AI/LLM integration and GenAI-enabled applications
• Experience with Messaging Systems such as Kafka or RabbitMQ
• Proficiency with Databases , including NoSQL (Cassandra, MongoDB) and SQL (PostgreSQL)
• Experience building and managing CI/CD pipelines (Jenkins, GitLab, or similar)
• Strong background in Unit & Integration Testing (JUnit, Spock, TestContainers)
• Experience with Cloud Platforms (AWS, GCP, Azure)
• Expertise in Containerization & Orchestration (Docker, Kubernetes)
• Strong understanding of Monitoring & Observability tools (Grafana, ELK, Prometheus)
• Solid grasp of Event-Driven Architecture patterns in distributed environments

Preferred Qualifications

• Proficiency in Python or Kotlin
• Experience with Legacy System Modernization and refactoring initiatives
• Knowledge of Security Best Practices , including OWASP standards and secure coding principles
• Familiarity with Agile methodologies such as Scrum or Kanban

Level:
6