Senior Engineer - Target India

Target Target · Retail · Bangalore, India

Senior Software Engineer to build the next generation of AI-powered engineering platforms using LLMs, RAG, and agent frameworks. This role involves designing, building, and operating production AI systems, focusing on AI platform engineering, backend services, distributed systems, observability, and cloud-native infrastructure. Responsibilities include developing scalable backend services with Java, driving platform architecture, and mentoring engineers.

What you'd actually do

  1. Design and build production-grade AI applications and platform capabilities using LLMs.
  2. Design and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval.
  3. Build and integrate AI agents using modern agent frameworks and Model Context Protocol (MCP).
  4. Develop scalable backend services using Java and Spring Boot.
  5. Build distributed systems that are reliable, observable, and fault tolerant.

Skills

Required

  • Java
  • Spring Boot
  • REST APIs
  • Microservices
  • Event-driven architectures
  • Kafka
  • PostgreSQL
  • Redis
  • Distributed systems
  • Prompt engineering
  • Structured prompting
  • Tool calling
  • Function calling
  • Evaluating and improving LLM quality
  • Designing and implementing RAG pipelines
  • Chunking strategies
  • Embedding generation
  • Vector databases
  • Retrieval optimization
  • Context management
  • Grounding and hallucination reduction
  • LangGraph
  • Spring AI
  • LangChain
  • CrewAI
  • Semantic Kernel
  • AutoGen
  • MCP Clients
  • MCP Servers
  • Tool development
  • Tool orchestration
  • Remote tool execution
  • Agent-to-tool integrations
  • Grafana
  • Prometheus
  • OpenTelemetry
  • ELK
  • Splunk
  • Logging
  • metrics
  • tracing

Nice to have

  • Knowledge Graphs
  • Neo4j
  • AI Evaluation frameworks
  • Prompt management
  • Multi-agent systems
  • Kubernetes
  • GCP
  • ServiceNow integrations
  • GitHub APIs
  • Slack APIs

What the JD emphasized

  • building and shipping at least two AI-powered applications or platform capabilities into production
  • practical, production experience - not just experimentation - with modern AI technologies
  • Experience integrating LLMs into production applications
  • Experience building AI agents using one or more of: LangGraph, Spring AI, LangChain, CrewAI, Semantic Kernel, AutoGen, Similar production agent frameworks
  • Experience with Model Context Protocol (MCP)

Other signals

  • building production-grade AI platforms
  • design, build, and operate production AI systems
  • modern LLM technologies
  • AI agent frameworks
  • RAG pipelines