Sr Engineer - AI Platforms / Context Intelligence (API's, search, information retrieval, agentic workflows)

Target • Brooklyn Park, NC

19d • Hybrid

About The Position

As a Senior Engineer on Target’s Context Intelligence team, you will help build the enterprise context and knowledge foundation that enables AI applications and agents to access, retrieve, and reason over trusted enterprise information. The role sits at the intersection of AI engineering, information retrieval, search, knowledge systems, and distributed platform engineering. You will design and build scalable context services for semantic and hybrid retrieval, grounding, memory, enterprise knowledge access, and AI experiences.

You will turn complex context and knowledge challenges into reusable platform capabilities, including retrieval services, memory systems, knowledge ingestion and indexing pipelines, context orchestration, and observability. As a senior engineering specialist, you will help shape application architecture, translate abstract architecture into concrete designs, implement robust and scalable systems, and influence fellow engineers through design guidance, code reviews, and technical mentorship.

The position uses a Hybrid/Flex for Your Day arrangement, with work performed both onsite at the assigned Target HQ location in Minnesota and virtually, depending on role, team, and daily tasks. Work duties cannot be performed outside the country of the primary work location unless otherwise prescribed by Target. The application deadline is November 19, 2026.

Requirements

• A four-year degree or equivalent experience.
• At least 5 years of software development experience with strong hands-on engineering and programming skills.
• Strong experience designing, building, testing, deploying, and operating production-grade applications, platform services, or distributed systems.
• Experience with information retrieval, search architecture, RAG, embeddings, vector databases, or related context and knowledge technologies.
• Strong proficiency in one or more modern programming languages and experience developing APIs, services, and data-intensive systems.
• Experience building or integrating semantic search, hybrid search, retrieval services, indexing pipelines, or enterprise search capabilities.
• Understanding of memory systems, context management, grounding, and retrieval patterns for LLM-powered or agentic applications.
• Strong understanding of distributed systems, stateful services, scalability, reliability, performance, security, and production operations.
• Experience with Kubernetes, containers, CI/CD, observability, testing, debugging, and operational monitoring.
• Experience with search infrastructure, distributed indexing, metadata systems, knowledge ingestion, or enterprise data connectors.
• Ability to clarify ambiguous requirements, understand AI systems’ context needs, and translate them into concrete technical designs and working software.
• Ability to evaluate retrieval and system tradeoffs across relevance, latency, freshness, scale, reliability, and cost.
• Strong problem-solving skills and ability to diagnose complex retrieval, indexing, and operational issues and prevent recurrence.
• Experience collaborating across organizational boundaries with platform, product, application engineering, architecture, and data teams.
• Ability to clearly communicate complex technical concepts, influence design decisions, mentor engineers, and raise engineering standards within a team.

Responsibilities

• Design, build, and operate scalable retrieval and context services that let AI applications and agents access trusted enterprise knowledge.
• Build semantic, hybrid, and enterprise search capabilities using information retrieval techniques, embeddings, vector databases, indexing, and search infrastructure.
• Develop retrieval-augmented generation (RAG) and grounding patterns to improve AI response relevance, quality, and trustworthiness.
• Build memory and context-management capabilities for conversational and agentic systems, including short- and long-term context and agent memory patterns.
• Design and implement enterprise knowledge ingestion, content indexing, metadata, synchronization, and connector capabilities to keep knowledge accessible and fresh.
• Build context orchestration services that select, assemble, and optimize information supplied to AI applications and agents.
• Develop retrieval observability and diagnostics covering grounding and retrieval quality, search metrics, freshness, performance, and operational health.
• Apply distributed systems and platform engineering principles to build reliable, scalable, secure, and maintainable stateful services and indexing systems.
• Design and operate containerized services on Kubernetes and contribute to resilient, multi-region architectures for enterprise-scale context and knowledge workloads.
• Evaluate retrieval, RAG, GraphRAG, knowledge graph, semantic technology, and enterprise search approaches through research and proof-of-concept activities.
• Lead code reviews, design reviews, testing, debugging, performance optimization, and architecture discussions while maintaining high engineering and operational standards.
• Partner with AI platform, application engineering, product, architecture, and data teams to understand context needs and translate them into reusable platform capabilities.
• Diagnose complex retrieval, indexing, grounding, memory, and production issues, identify systemic causes, and develop solutions that prevent recurrence.
• Share technical patterns and best practices and help engineering teams adopt Context Intelligence platform capabilities.
• Maintain technical knowledge and stay current with retrieval, knowledge, AI, and platform technologies through formal training and self-directed learning.

Benefits

• Eligible team members and dependents may receive comprehensive health benefits and programs, which may include medical, vision, dental, and life insurance.
• 401(k).
• Employee discount.
• Short-term disability.
• Long-term disability.
• Paid sick leave.
• Paid national holidays.
• Paid vacation.
• Additional financial, education, and well-being benefits may be available to eligible team members.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior