Sr Engineer - Target India

Target Target · Retail · Bangalore, India

Senior Engineer role focused on integrating LLMs and GenAI features into core applications, building agentic frameworks, and improving AI reliability within an enterprise retail context. Requires strong backend development skills in Java/Python, microservices, and cloud technologies, with an emphasis on AI/LLM integration and automation.

What you'd actually do

  1. Designing scalable architecture with the best choice of tech, responsible for all the services/functionalities that the team develops while ensuring quality of the team's code and/or infrastructure standards.
  2. Hands-on development, often taking on the more complicated tasks. Ensures solution is production ready, deployable, scalable and resilient.
  3. Planning and delivering of work in the team in addition to their own work. Promotes a learning culture through mentoring and coaching.
  4. Ensures product observability is in place for reliability. Fosters a culture of observability across teams and helps use operational data to improve stability and performance of their domains. Drives monitoring work on their team based on the organization's monitoring philosophy. Is aware of the operational data for their team’s domain and uses it as a basis for driving changes to the team's services to achieve stability and performance improvements.
  5. Responsible for ensuring the security of the product and fostering a security first mindset across teams. Highly skilled with applying and implementing security concepts such as identifying vulnerabilities in software, creating logic to detect malicious behavior, and analyzing network or host artifacts.
  6. Integrate Large Language Models (LLMs) and GenAI-powered features into core applications.
  7. Build robust systems that mitigate hallucinations and improve AI reliability.
  8. Experience building agentic frameworks and AI-driven automation for process enhancement

Skills

Required

  • Java & Python
  • Microservices Architecture
  • Spring Boot or Micronaut
  • AI / LLM Integration
  • AI Reliability & Automation
  • Messaging Systems (Kafka, RabbitMQ)
  • Databases (NoSQL like Cassandra, MongoDB, SQL like PostgreSQL)
  • CI/CD (Jenkins, GitLab)
  • Unit and Integration Testing (Spock, JUnit, TestContainers for Java; PyTest, Unittest for Python)
  • Cloud Services (AWS, GCP, Azure)
  • Containerization and Orchestration (Docker, Kubernetes)
  • Monitoring & Observability (Grafana, ELK Stack, Prometheus)
  • Event-Driven Architecture

Nice to have

  • Functional Programming (Kotlin)
  • GraphQL
  • Legacy System Modernization
  • Security Best Practices (OWASP, vulnerability scanning, secure coding principles)
  • Agile Methodologies

What the JD emphasized

  • AI / LLM Integration
  • AI Reliability & Automation
  • agentic frameworks
  • AI-driven automation
  • Large Language Models (LLMs)
  • GenAI-powered features
  • mitigate hallucinations
  • improve AI reliability
  • building agentic frameworks
  • AI-driven automation for process enhancement

Other signals

  • Integrate Large Language Models (LLMs) and GenAI-powered features into core applications.
  • Build robust systems that mitigate hallucinations and improve AI reliability.
  • Experience building agentic frameworks and AI-driven automation for process enhancement.