Sr Engineer - Ad Tech

Target is hiring a Sr Engineer - Ad Tech in Bangalore.

Responsibilities

As a Senior Engineer - AI Platform, you will be a senior individual contributor responsible for designing and building production-grade AI capabilities and helping shape the technical direction of the platform. You will work hands-on across LLM applications, RAG, AI agents, MCP, Java/Kotlin and distributed systems, translating emerging AI capabilities into reliable software that can operate at scale. The role is a combination of strong software engineering and practical AI engineering. You will be expected to make sound architectural decisions, solve complex technical problems, contribute to engineering standards, and mentor other engineers. The key to success in this role is having real production experience building and shipping AI applications, not just experimenting with LLMs or proof-of-concepts. Use your skills, experience, and talents to be a part of groundbreaking thinking and visionary goals.

AI Engineering & Agentic Systems

• LLM Applications: Build and integrate production-grade applications using large language models, including prompt engineering, model integration, structured outputs, and inference workflows.
• RAG: Design and implement Retrieval-Augmented Generation solutions covering retrieval, embeddings, metadata filtering, reranking, grounding, citations, and evaluation.
• AI Agents: Build agentic workflows using agent frameworks and tool-enabled architectures, including Model Context Protocol (MCP) and multi-step agent interactions.
• Agent Architecture: Design reliable patterns for agent, tool, and service interactions with clear separation of responsibilities and measurable execution behavior.
• Evaluation & Quality: Build approaches to evaluate AI systems for correctness, reliability, grounding, tool usage, and regression across model and prompt changes.

Software Engineering & Architecture

• System Design: Design scalable, resilient distributed systems that support AI workloads and high-volume production use cases.
• Java / Kotlin Engineering: Build backend services using Java or Kotlin, Spring Boot, microservices, APIs, and cloud-native patterns.
• Architecture: Drive design decisions for core platform components, balancing performance, scalability, maintainability, and operational requirements.
• Code Quality & Mentorship: Raise engineering standards through thoughtful code reviews, design reviews, mentoring, and strong implementation practices.

Requirements

• Education: 4-year degree in Computer Science, Engineering, or equivalent practical experience.
• Experience: 4–7 years of software engineering experience, with meaningful experience as a senior individual contributor.
• AI Experience: Hands-on experience building and shipping LLM-powered or agentic applications into production.
• LLM / GenAI: Strong experience with LLM integration, prompt engineering, structured outputs, and production AI application patterns.
• RAG: Practical experience building RAG systems, including retrieval, embeddings, metadata filtering, reranking, grounding, and evaluation.
• Agentic AI: Experience with AI agent frameworks, tool calling, agent orchestration, MCP, or similar agentic architectures.
• Backend Engineering: Strong proficiency in Java/Kotlin and Spring Boot, with experience building APIs and distributed services.
• Distributed Systems: Strong understanding of microservices, asynchronous systems, APIs, resilience, scalability, and failure handling.
• Reliability & Observability: Hands-on experience building production systems with monitoring, logging, metrics, alerting, and operational readiness.
• Cloud & DevOps: Experience with cloud-native environments and technologies such as Kubernetes, Docker, CI/CD, and managed cloud services.
• Engineering Practices: Strong coding, debugging, design, testing, code review, and problem-solving skills.

Desired Qualifications

• Experience building multi-agent systems or agent-to-agent architectures.
• Experience with Model Context Protocol (MCP) or similar tool/context integration patterns.
• Experience with vector databases, embedding systems, reranking, or modern retrieval infrastructure.
• Experience designing AI evaluation frameworks, including deterministic evaluation, LLM-based evaluation, and production regression testing.

About Target

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. At Target, we have a timeless purpose and a proven strategy, and that hasn’t happened by accident. Some of the best minds from diverse backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India op