Samsung AI Process Innovation Manager

2020 Companies•Plano, TX

1d•Onsite

About The Position

The Manager, AI Process Innovation, designs, develops, and deploys Agentic AI solutions and process automation workflows within Samsung's SEA Process Innovation Group. This role bridges AI technology and business operations, translating identified use cases into working production systems that drive measurable improvements in Care service quality and efficiency. This position collaborates closely with the Sr. Manager, Korea HQ counterparts, and SEA business unit stakeholders to ensure AI implementations align with strategic priorities and are delivered on time and within scope.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Information Systems, or related field
5–8 years of experience in software development, process automation, or AI/ML implementation
Hands-on experience building and deploying Agentic AI systems in production — including multi-agent orchestration, tool integration, and autonomous task execution (required)
Proficiency in Python; experience with AI/ML libraries (LangChain, LangGraph, AutoGen, OpenAI SDK, Hugging Face Transformers)
Experience designing and building MCP (Model Context Protocol) servers and connecting agents to enterprise APIs and databases
Strong API development and integration skills: REST, GraphQL, OAuth2/JWT authentication, API gateway configuration
Database experience: vector databases (Pinecone, Weaviate, Chroma, pgvector), relational databases (PostgreSQL, MySQL), NoSQL (MongoDB, Redis)
Experience with cloud AI services: Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent
Experience with containerization and deployment: Docker, Kubernetes, CI/CD pipelines (GitHub Actions, Azure DevOps)
Ability to clearly communicate technical designs and implementation status to non-technical business stakeholders
Self-directed and results-oriented; comfortable managing multiple concurrent workstreams
Skilled in use of Microsoft Office, including Excel, PowerPoint, and Word
Willing to work on-site at the Dallas, TX office
Bilingual in English and Korean
Applicants must be authorized to work in the United States full-time without current or future visa sponsorship.

Nice To Haves

Low-code development experience (Microsoft Power Platform, Appian, or equivalent) preferred
Background in Customer Service, Care operations, or service industry processes strongly preferred
Korean language proficiency preferred for collaboration with Korea HQ

Responsibilities

Agentic AI Development: Design, build, and deploy multi-agent AI workflows using frameworks such as LangGraph, AutoGen, or CrewAI; implement agent orchestration, tool-calling, memory, and guardrail logic for production Care operation use cases
AI Use Case Discovery & Implementation: Identify, document, and prioritize AI use cases in collaboration with business stakeholders across Care functions (contact center automation, intelligent case routing, knowledge assistant, quality monitoring); lead full implementation lifecycle from PoC through production
MCP Server Development: Develop and maintain MCP (Model Context Protocol) servers that expose enterprise data and capabilities to AI agents; design tool definitions, authentication, and response schemas
API & System Integration: Build and maintain API integrations connecting AI agents to internal systems (CRM, ticketing, ERP, knowledge bases) and external services; develop RESTful APIs and webhook handlers
Database Design & Management: Design and manage databases supporting AI applications: configure vector stores for RAG pipelines, maintain relational schemas for application data, and optimize query performance for real-time AI inference
Low-Code Automation: Develop process automation solutions using low-code platforms (e.g., Microsoft Power Automate, Power Apps, or equivalent) to accelerate delivery of repetitive process improvements
Environment Configuration: Set up and maintain full AI development and production environments: LLM API configuration, containerization (Docker/Kubernetes), CI/CD pipelines, monitoring dashboards, and logging infrastructure
Process Analysis & Improvement: Conduct as-is process mapping and gap analysis for target business processes; translate findings into AI-augmented to-be designs and document implementation specifications
Quality Assurance & Governance: Develop evaluation frameworks for AI agent outputs; monitor production model performance, hallucination rates, and latency; implement feedback loops and continuous improvement cycles