About us:
Target is an iconic brand, a Fortune 50 company and one of America’s leading retailers.
Target as a tech company? Absolutely. We’re the behind-the-scenes powerhouse that fuels Target’s passion and commitment to cutting-edge innovation. We anchor every facet of one of the world’s best-loved retailers with a strong technology framework that relies on the latest tools and technologies—and the brightest people—to deliver incredible value to guests online and in stores. Target Technology Services is on a mission to offer the systems, tools and support that guests and team members need and deserve. Our high-performing teams balance independence with collaboration, and we pride ourselves on being versatile, agile and creative. We drive industry-leading technologies in support of every angle of the business, and help ensure that Target operates smoothly, securely and reliably from the inside out.
About the Team
Synapse is the AI-powered operational intelligence platform for Roundel Engineering. Our mission is to help engineering teams detect, investigate, understand, and resolve production issues faster by combining AI with observability, knowledge retrieval, business intelligence, and modern agent frameworks.
The platform integrates with systems such as Grafana, TAP, ServiceNow, GitHub, Slack, Hawk-I, and data observability platforms while leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and multi-agent architectures to automate operational workflows.
We're looking for engineers who enjoy building production-grade AI platforms - not prototypes.
About the Role
We are looking for a Senior Software Engineer who will help build the next generation of AI-powered engineering platforms.
This is a hands-on engineering role where you'll design, build, and operate production AI systems using modern LLM technologies while solving complex distributed systems problems.
You'll work across AI platform engineering, backend services, distributed systems, observability, and cloud-native infrastructure to build scalable and reliable AI capabilities for engineering teams. This role requires someone who enjoys writing production code, making architectural decisions, mentoring engineers, and driving technical excellence.
What You'll Do
- Design and build production-grade AI applications and platform capabilities using LLMs.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines for enterprise knowledge retrieval.
- Build and integrate AI agents using modern agent frameworks and Model Context Protocol (MCP).
- Develop scalable backend services using Java and Spring Boot.
- Build distributed systems that are reliable, observable, and fault tolerant.
- Design APIs and platform services used across multiple engineering teams.
- Drive platform architecture and engineering standards.
- Improve platform reliability, security, scalability, and performance.
- Participate in production support, incident analysis, and platform hardening.
- Mentor engineers through design reviews, code reviews, and technical guidance.
- Collaborate with Product, SRE, Platform, and Data Engineering teams.
What We're Looking For
Experience
- 4 - 7 years of professional software engineering experience.
- Experience as a senior individual contributor designing and delivering production software.
- Demonstrated experience building and shipping at least two AI-powered applications or platform capabilities into production.
- Strong experience developing scalable backend systems using Java.
- Experience building cloud-native distributed systems.
Required Technical Skills
AI Engineering
We're looking for engineers who have practical, production experience - not just experimentation - with modern AI technologies.
Large Language Models (LLMs)
- Experience integrating LLMs into production applications.
- Strong prompt engineering skills.
- Experience with structured prompting, tool calling, and function calling.
- Experience evaluating and improving LLM quality.
Retrieval-Augmented Generation (RAG)
- Designing and implementing RAG pipelines.
- Chunking strategies.
- Embedding generation.
- Vector databases.
- Retrieval optimization.
- Context management.
- Grounding and hallucination reduction.
AI Agent Frameworks
Experience building AI agents using one or more of:
- LangGraph
- Spring AI
- LangChain
- CrewAI
- Semantic Kernel
- AutoGen
- Similar production agent frameworks
Model Context Protocol (MCP)
Experience with:
- MCP Clients
- MCP Servers
- Tool development
- Tool orchestration
- Remote tool execution
- Agent-to-tool integrations
Backend Engineering
Strong experience with
- Java (17+ preferred)
- Spring Boot
- REST APIs
- Microservices
- Event-driven architectures
- Kafka
- PostgreSQL
- Redis
- Distributed systems
Observability
Experience building observable systems using technologies such as
- Grafana
- Prometheus
- OpenTelemetry
- ELK
- Splunk
- Logging, metrics, tracing
More importantly, you understand why instrumentation matters and how observability contributes to reliable software.
Nice to Have
- Knowledge Graphs
- Neo4j
- Vector databases
- AI Evaluation frameworks
- Prompt management
- Multi-agent systems
- Kubernetes
- GCP
- ServiceNow integrations
- GitHub APIs
- Slack APIs
What Success Looks Like
First 90 Days
- Understand the Roundel Synapse architecture.
- Deliver production-quality features independently.
- Contribute to platform design discussions.
- Participate in code reviews and production support.
Within 6 Months
- Own the design and implementation of a significant platform capability.
- Deliver at least one architectural improvement into production.
- Improve platform reliability, scalability, or engineering productivity.
- Lead production hardening efforts for owned components.
- Successfully onboard at least two engineering teams onto the platform.
- Become a technical mentor for other engineers.
What Makes Someone Successful Here
We're looking for engineers who
- Think like platform builders rather than feature developers.
- Take ownership from design through production.
- Enjoy solving ambiguous engineering problems.
- Balance speed with long-term maintainability.
- Raise the engineering bar through code quality, architecture, and mentoring.
- Are curious about AI but grounded in strong software engineering fundamentals.
Why Join Us
You'll have the opportunity to build one of Roundel's flagship AI platforms while working on cutting-edge technologies including LLMs, RAG, AI agents, observability, and distributed systems. The work you do will directly improve engineering productivity and operational excellence across the organization.
Skills Required
- 4-7 years professional software engineering experience
- Experience as a senior individual contributor designing and delivering production software
- Built and shipped at least two AI-powered applications or platform capabilities into production
- Experience integrating Large Language Models (LLMs) into production applications
- Strong prompt engineering skills (structured prompting, tool/function calling, LLM quality evaluation)
- Designing and implementing Retrieval-Augmented Generation (RAG) pipelines including chunking, embeddings, and retrieval optimization
- Experience with embedding generation and vector databases
- Experience building AI agents using modern agent frameworks (e.g., LangChain, LangGraph, Spring AI, CrewAI, Semantic Kernel, AutoGen)
- Experience with Model Context Protocol (MCP) including clients, servers, tool development and orchestration
- Strong backend engineering with Java (17+ preferred) and Spring Boot
- Design and implement REST APIs, microservices, and event-driven architectures
- Experience with Kafka for event-driven systems
- Experience with PostgreSQL and Redis
- Experience building cloud-native distributed systems (scalability, reliability, fault tolerance)
- Experience with observability tooling and instrumentation (Grafana, Prometheus, OpenTelemetry, ELK, Splunk)
- Participation in production support, incident analysis, and platform hardening
- Mentoring engineers via design reviews, code reviews, and technical guidance
- Knowledge of retrieval context management and hallucination reduction strategies
- Knowledge Graphs and Neo4j
- AI evaluation frameworks, prompt management, and multi-agent systems
- Kubernetes and GCP experience
- ServiceNow, GitHub, and Slack integrations/APIs
Target Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Target and has not been reviewed or approved by Target.
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Healthcare Strength — Health benefits are accessible to hourly team members at relatively low hour thresholds and include no‑cost, 24/7 virtual medical care and expanded mental‑health support. This breadth is positioned as a relative strength compared to typical retail offerings.
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Retirement Support — Retirement programs include a dollar‑for‑dollar 401(k) match with immediate vesting and options like Roth 401(k) and stock purchase. These features strengthen long‑term savings for a wide range of roles.
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Parental & Family Support — Family support includes paid family leave, backup care, and reimbursements for adoption and surrogacy. These resources complement paid time off and holidays for eligible team members.
Target Insights
What We Do
Target is an American retailing company providing access to a wide selection of products such as furniture, electronics, toys, and more. Target is one of the world’s most recognized brands and one of America’s leading retailers. We make Target our guests’ preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver. Target is committed to responsible corporate citizenship, ethical business practices, environmental stewardship and generous community support. Since 1946, we have given 5 percent of our profits back to our communities. Our goal is to work as one team to fulfill our unique brand promise to our guests, wherever and whenever they choose to shop.





