Lead Engineer Target India-2

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

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 Targets 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 inJava including backend systems and automation workflows
Strong experience inMicroservices Architectureand distributed systems
Expertise withSpring Boot or Micronaut including reactive programming models
Hands-on experience withAI/LLM integrationand GenAI-enabled applications
Experience withMessaging Systemssuch as Kafka or RabbitMQ
Proficiency withDatabases including NoSQL (Cassandra MongoDB) and SQL (PostgreSQL)
Experience building and managingCI/CD pipelines(Jenkins GitLab or similar)
Strong background inUnit & Integration Testing(JUnit Spock TestContainers)
Experience withCloud Platforms(AWS GCP Azure)
Expertise inContainerization & Orchestration(Docker Kubernetes)
Strong understanding ofMonitoring & Observabilitytools (Grafana ELK Prometheus)

Solid grasp ofEvent-Driven Architecturepatterns in distributed environments

Preferred Qualifications
Proficiency inPython or Kotlin
Experience withLegacy System Modernizationand refactoring initiatives
Knowledge ofSecurity Best Practices including OWASP standards and secure coding principles

Familiarity withAgile methodologiessuch as Scrum or Kanban

Required Experience:

Lead Engineer Role & ResponsibilitiesAs 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 en...

Technology Evaluation & Innovation
- Evaluate emerging technologies and contribute to architectural decision-making considering alignment with Targets 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.