Sr Engineer - Gift Card Platform

Target•Brooklyn Park, NC

41d•Hybrid

About The Position

As a Senior Engineer on the Gift Card Platform team, you'll design and build highly scalable, reliable platform capabilities that power critical Gift Card experiences across Target. You'll combine strong backend and distributed systems engineering expertise with modern AI application development to build the next generation of intelligent, AI-ready platform capabilities. You'll serve as a technical leader, shaping architecture, influencing implementation decisions, and establishing engineering best practices. You'll work across APIs, data, events, integrations, large-scale file and data processing, distributed systems, and guest-facing backend capabilities, while also helping evolve the platform with domain AI agents, MCP tools and services, and agentic workflows. You are equally comfortable solving complex distributed systems problems and applying emerging AI technologies where they create meaningful value. You bring strong software engineering fundamentals and build production systems that are secure, scalable, resilient, observable, and maintainable. Use your skills, experience and talents to be a part of groundbreaking thinking and visionary goals.

Requirements

4 year degree or equivalent experience
5+ years of software development experience
Demonstrates strong domain-specific knowledge regarding Target’s technology capabilities, and key competitors’ products and differentiating features
Working knowledge on package-specific configuration and deployment along with ability to build custom solutions
Designs new testing methods and resolves routine and non-routine technical issues with minimal assistance
Demonstrates strong proficiency in core development platforms within own domain
Builds strong commitment within the team to support the appropriate team priorities
Clearly communicates Agile concepts to partners within product team
Demonstrates a solid understanding of the impact of own work on the team and/or guests
Writes and organizes code using multiple computer languages, including distributed programming and understand different frameworks and paradigm
Delivers high-performance, scalable, repeatable, and secure deliverables with broad impact (high throughput and low latency)
Influences and applies data standards, policies, and procedures
Maintains technical knowledge within areas of expertise
Stays current with new and evolving technologies via formal training and self-directed education
Strong proficiency in Kotlin and/or Java, with experience building backend services using Micronaut, Spring Boot, or similar frameworks
Experience designing distributed systems and service-oriented architectures, including REST and/or GraphQL APIs, event-driven architectures, asynchronous messaging, and webhooks
Experience building large-scale data and file processing capabilities, including high-volume data access, transformation, asynchronous processing, fault recovery, and performance optimization
Experience with relational databases such as PostgreSQL and distributed caching technologies such as Redis, including data modeling, indexing, transactions, query optimization, and high-performance data access patterns
Experience with Docker, Kubernetes, cloud-native architectures, and modern CI/CD pipelines
Experience building and operating highly available and resilient production systems, with an understanding of data consistency, fault tolerance, observability, and production operations
Experience designing or building AI-powered applications, tools, or agentic workflows using modern Large Language Models (LLMs) and related AI technologies
Understanding of modern AI application architecture and practices, including prompt and context engineering, Retrieval-Augmented Generation (RAG), tool calling, agent orchestration, MCP, and AI evaluation
Experience applying security, privacy, governance, reliability, observability, and cost considerations to production AI applications
Proficiency in Python for AI application development, automation, or AI tooling
Experience effectively leveraging AI-assisted engineering tools and workflows while maintaining strong standards for code quality, security, architecture, testing, and maintainability
Demonstrates strong technical leadership and collaboration skills, including mentoring engineers, leading technical design discussions, influencing architecture, and translating complex business and technical problems into scalable engineering solutions

Responsibilities

Use your technology acumen to apply and maintain knowledge of current and emerging technologies within specialized area(s) of the technology domain.
Evaluate new technologies and participate in decision-making, accounting for factors such as viability within Target’s technical environment, maintainability, and cost of ownership.
Initiate and execute research and proof-of-concept activities for new technologies.
Lead the design, lifecycle management, and total cost of ownership of services.
Design and build highly scalable platform capabilities and backend services using Kotlin, Java, and Micronaut, including secure, high-performance REST and GraphQL APIs.
Design distributed and event-driven systems using Kafka, asynchronous messaging, webhooks, distributed caching, and cloud-native architecture patterns.
Build scalable data and file processing capabilities that support high-volume workloads with strong resiliency and fault tolerance.
Design and optimize data persistence and caching solutions using technologies such as PostgreSQL and Redis, including data modeling, indexing, query optimization, transactional integrity, and high-performance data access patterns.
Lead functional design and architecture discussions, code and design reviews, testing, debugging, automation, and implementation activities, ensuring architectural and operational requirements and engineering best practices are met.
Build and operate highly available, secure, resilient, and observable P1 services and platforms.
Improve performance and operational health through distributed tracing, metrics, logging, monitoring, and continuous improvement.
Apply AI-assisted software development tools throughout the software development lifecycle, including design, implementation, testing, debugging, documentation, and code review, while maintaining high standards for quality, security, architecture, and maintainability.
Design and build production-grade AI capabilities using Target-approved technologies, including domain AI agents, agentic workflows, MCP tools and services, and Retrieval-Augmented Generation (RAG).
Apply prompt and context engineering, tool integration, and AI evaluation practices to improve quality, reliability, and relevance.
Optimize AI capabilities for quality, latency, throughput, reliability, and cost while applying responsible AI, security, privacy, governance, and observability practices.
Build reusable AI components and identify opportunities to improve platform capabilities, developer productivity, operations, and engineering workflows.
Provide technical oversight and coach others to resolve complex and severe technical issues.
Partner across engineering and product teams to influence technical direction, establish engineering best practices, and deliver scalable solutions.
Lead disaster recovery activities and contribute to disaster recovery planning.
Embed data quality protocols throughout data acquisition, processing, storage, and operational use.