The Role
Design, build, and deploy AI/ML and generative-AI capabilities for a device management platform, including LLM-driven search, conversational assistants, anomaly detection, predictive insights, RAG/vector search, CI/CD pipelines, and integrations with backend and enterprise systems. Lead architecture, evaluation, governance, and operationalization of AI solutions across product, security, and infrastructure teams.
Summary Generated by Built In
We are looking for an AI Engineer to help transform our Device Management Platform through the adoption of intelligent, AI-powered capabilities. This role will focus on designing, developing, and integrating AI solutions that improve how enterprise devices are managed, monitored, and supported at scale.
You will work closely with product, engineering, security, and infrastructure teams to identify high-value use cases and build solutions such as intelligent search, conversational assistants, anomaly detection, predictive insights, automated remediation, and AI-driven operational analytics. The ideal candidate combines strong software engineering fundamentals with practical experience building and integrating AI/ML and Generative AI solutions into production systems.
Core ResponsibilitiesAI Solution Development- Design, develop, and deploy AI-powered capabilities across the Device Management Platform
- Build intelligent search experiences leveraging LLMs, semantic search, vector databases, and retrieval-augmented generation (RAG)
- Build and maintain MCP tools and integrations for device management, compliance, ITSM, etc.
- Develop AI-driven insights using device telemetry, operational metrics, and platform data
- Implement conversational experiences and AI assistants that simplify device management workflows
- Build AI features for compliance evaluation, anomaly detection, natural-language admin commands, and self-healing using language models and local RAG.
- Implement the confidence gateway that converts probabilistic AI decisions into deterministic actions with policy thresholds, guardrails, audit logs, and human-approval paths.
- Develop scalable services and APIs that integrate AI capabilities into existing platform workflows
- Build data pipelines and retrieval systems to support AI applications
- Evaluate and integrate foundation models, LLMs, embeddings, and agent frameworks
- Design and implement prompt engineering, evaluation, and observability frameworks
- Ensure AI solutions are secure, reliable, scalable, and cost-effective
- Integrate AI capabilities with device management services, backend platforms, and enterprise systems
- Collaborate with platform teams to operationalize AI solutions in production environments
- Build and maintain CI/CD pipelines supporting AI applications and services
- Partner with infrastructure teams to optimize AI workloads and deployments
- Identify opportunities to leverage AI to improve operational efficiency and user experience
- Establish best practices for AI solution design, model evaluation, governance, and responsible AI usage
- Contribute to architectural decisions around scalability, reliability, security, and AI adoption
- Partner with product, engineering, security, infrastructure, and business teams to identify AI use cases and prioritize investments
- Translate business problems into AI-powered solutions
- Communicate technical concepts and AI recommendations to both technical and non-technical stakeholders
- Stay current with emerging AI technologies and bring innovative ideas into the platform
- 4+ years of software engineering experience, including experience building production-grade applications and services
- Hands-on experience developing and deploying AI-powered applications or Generative AI solutions
- Experience building applications using Large Language Models (LLMs) such as OpenAI GPT, Claude, Gemini, Llama, or similar models
- Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search
- Understanding of model confidence, evaluation metrics, false positives/negatives, and safe fallback behaviour.
- Familiarity with AI governance, explainability, and approval-gated automation for high-risk actions.
- Exposure to Anomaly detection, Confidence scoring and decision thresholds, Explainability and Auditability
- Strong proficiency in Python, Java, Kotlin, or a combination thereof
- Experience designing and implementing REST APIs and backend service integrations
- Experience working with cloud-based AI services and AI development frameworks
- Experience evaluating AI solutions and measuring quality through testing, experimentation, and monitoring
- Strong understanding of software engineering best practices, CI/CD, testing, and observability
- Strong problem-solving skills and ability to work across cross-functional teams
- Experience working with enterprise device management platforms, Android Enterprise, IoT systems, or edge devices
- Experience building intelligent search, recommendation engines, chatbots, or AI assistants
- Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar AI frameworks
- Experience leveraging device telemetry and operational data to build predictive analytics or anomaly detection solutions
- Familiarity with Temporal or similar workflow orchestration frameworks
- Experience with event-driven architectures and distributed systems
- Knowledge of responsible AI practices, model governance, and AI security
Skills Required
- 4+ years of software engineering experience building production-grade applications and services.
- Hands-on experience developing and deploying AI-powered applications or Generative AI solutions.
- Experience building applications using LLMs such as OpenAI GPT, Claude, Gemini, Llama, or similar.
- Experience with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and semantic search.
- Understanding of model confidence, evaluation metrics, false positives/negatives, and safe fallback behaviour.
- Familiarity with AI governance, explainability, and approval-gated automation for high-risk actions.
- Exposure to anomaly detection, confidence scoring and decision thresholds, explainability and auditability.
- Strong proficiency in Python, Java, Kotlin, or a combination thereof.
- Experience designing and implementing REST APIs and backend service integrations.
- Experience working with cloud-based AI services and AI development frameworks.
- Experience evaluating AI solutions and measuring quality through testing, experimentation, and monitoring.
- Strong understanding of software engineering best practices, CI/CD, testing, and observability.
- Strong problem-solving skills and ability to work across cross-functional teams.
- Experience with enterprise device management platforms, Android Enterprise, IoT systems, or edge devices.
- Experience building intelligent search, recommendation engines, chatbots, or AI assistants.
- Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar AI frameworks.
- Experience leveraging device telemetry and operational data to build predictive analytics or anomaly detection solutions.
- Familiarity with Temporal or similar workflow orchestration frameworks.
- Experience with event-driven architectures and distributed systems.
- Knowledge of responsible AI practices, model governance, and AI security.
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.
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The Company
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.
