Engineer - Target India-8

Working at Target means helping all families discover the joy of everyday life. That purpose drives everything we build—especially our technology. Our teams create scalable, reliable systems that power meaningful guest and team member experiences.

About the Role

As an Engineer, you’ll build the technology behind our products—focusing on scalable backend systems, modern engineering practices, and emerging AI capabilities.

You’ll work closely with your team to design, build, and improve services, while balancing speed, quality, and reliability. You’ll also contribute to code quality, system design, and day-to-day operations with a strong sense of ownership.

What You’ll Do

Build and improve backend services and microservices

Work on distributed systems and data pipelines

Design and develop APIs; contribute to full-stack integrations when needed

Write clean, maintainable, and production-ready code

Monitor systems, troubleshoot issues, and handle production support

Participate in code reviews and design discussions to improve quality

Explore and help evolve the GenAI/ML capabilities in applications

What We’re Looking For

Basic Qualifications

Bachelor’s degree in Computer Science or equivalent experience

2–4 years of relevant software engineering experience

Must-Have (Core Skills)

Strong programming skills in one language (Python, Java, Kotlin, or JavaScript/TypeScript)

Solid understanding of:

APIs and microservices

Data structures and problem-solving

Basic system design and distributed systems concepts

Experience with modern development practices (CI/CD, version control, testing)

Ability to independently own and deliver features end-to-end

Willingness to learn, adapt, and grow in a fast-paced environment

Good-to-Have (Differentiators)

Experience with distributed data systems (Kafka, Spark, etc.)

Hands-on with Docker, Kubernetes, or infrastructure-as-code tools

Experience with SQL or NoSQL databases

Exposure to frontend technologies (React, TypeScript, etc.)

Experience working on production systems at scale

AI / ML Exposure (a strong plus):

Working with LLM APIs, prompt engineering

Understanding of RAG, embeddings, or vector databases

Familiarity with ML tools (MLflow, Airflow, etc.)

Exposure to agent-based frameworks (LangChain, AutoGen, etc.)

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