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Vector Databases Jobs in Marion, OH (NOW HIRING)

The Scotts Miracle-Gro Company

Agent Engineer

Marysville, OH · On-site

$13.75 - $18.50/hr

LLMs (GPT-4, Claude, Gemini), prompt engineering, RAG, vector databases, and agent orchestration (LangChain, Flowise, or similar). • Ability to learn new platforms quickly -- you will ramp on ...

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Vector Databases information

What are vector databases?

Vector databases are specialized databases designed to store, manage, and search high-dimensional vector data, which is commonly generated from machine learning models, such as embeddings from natural language processing or image recognition. They enable efficient similarity search operations, such as finding the most similar items to a given query vector, which is essential for applications like recommendation systems, semantic search, and AI-powered search engines. Unlike traditional databases that handle structured or unstructured data, vector databases are optimized for fast and scalable similarity searches on large datasets of vectors.

What are some common challenges faced when working with vector databases, and how can they be addressed?

Professionals working with vector databases often encounter challenges such as efficiently scaling to handle large datasets, ensuring low-latency similarity searches, and integrating the database with machine learning pipelines. To address these, teams typically implement distributed architectures, fine-tune indexing strategies, and collaborate closely with data engineers and machine learning specialists. Staying updated with the latest developments in vector database technologies and maintaining clear communication with cross-functional teams are also key to overcoming these challenges.

What are the key skills and qualifications needed to thrive as a vector database engineer, and why are they important?

Success as a Vector Database Engineer requires a strong background in computer science, database management, and experience with machine learning or AI-driven data systems. Familiarity with vector database platforms (such as Pinecone, Milvus, or Weaviate), cloud infrastructure, and proficiency in languages like Python are typically expected. Strong problem-solving skills, effective communication, and the ability to work cross-functionally help engineers stand out. These competencies are vital to efficiently design, deploy, and maintain scalable vector search solutions that power modern AI applications.

What is the difference between Vector Databases vs Data Engineers?

AspectVector DatabasesData Engineers
Required SkillsDatabase management, data modeling, query optimizationData pipeline development, ETL processes, programming
Work EnvironmentData storage systems, AI/ML projects, cloud platformsData infrastructure, cloud environments, big data tools
Industry UsageAI, machine learning, recommendation systemsData integration, analytics, data architecture

While Vector Databases focus on storing and querying high-dimensional vector data for AI applications, Data Engineers build and maintain data pipelines and infrastructure to support data analysis and machine learning workflows. Both roles are essential in data-driven industries but serve different functions within the data ecosystem.

What cities near Marion, OH are hiring for Vector Databases jobs?

Cities near Marion, OH with the most Vector Databases job openings:

Vector Databases jobs near you
Infographic showing various Vector Databases job openings in Marion, OH as of August 2026, with employment types broken down into 83% Full Time, 11% Part Time, and 6% Contract. Highlights an 83% Physical, 6% Hybrid, and 11% Remote job distribution.

Agent Engineer

The Scotts Miracle-Gro Company

Marysville, OH • On-site

$13.75 - $18.50/hr

Full-time

Re-posted 8 days ago

ScottsMiracle-Gro rating

7.4

Company rating: 7.4 out of 10

Based on 59 frontline employees who took The Breakroom Quiz

298th of 544 rated manufacturers

Job description

Job Summary:
The Scotts Miracle-Gro Company is a leader in the gardening industry, and they are seeking an Agent Engineer to own the AI agent development lifecycle. This role involves designing and delivering production-grade AI agents to solve business challenges across customer service and internal workflows.
Responsibilities:
• Own end-to-end agent development — from requirements and design through pilot, deployment, monitoring, and iterative improvement.
• Build production-grade AI agents using Sierra and complementary tools (LangChain, ADK, or similar orchestration frameworks) for customer-facing and internal use cases.
• Design agent architectures: conversation flows, tool use, RAG integration, human handoff logic, and multi-channel deployment (chat, SMS, voice, email).
• Implement prompt engineering, guardrails, and evaluation pipelines to ensure agents meet quality, safety, and brand standards.
• Become the in-house expert on Sierra and related agent platforms — learn the Agent SDK, Agent Studio, and deployment options to maximize platform value.
• Evaluate when to use platform-native capabilities vs. custom extensions; recommend build vs. buy vs. configure for new agent use cases.
• Integrate agents with SMG systems: CRM, e-commerce, knowledge bases, and internal tools. Ensure secure, compliant access to data and APIs.
• Establish reusable patterns, templates, and best practices for agent development that the CoE and FDEs can leverage.
• Partner with Digital and CS teams to identify high-value agent opportunities and define success metrics.
• Track agent performance (resolution rates, satisfaction, deflection, latency) and drive continuous improvement based on data and user feedback.
• Document agent designs, runbooks, and operational procedures. Support responsible AI practices and governance requirements.
Qualifications:
Required:
• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.
• 3+ years of software engineering experience, with 1+ years building or integrating AI/LLM-powered applications or agents.
• Strong programming fundamentals — Python required; experience with React, TypeScript/JavaScript and API design is a plus.
• Hands-on experience with generative AI: LLMs (GPT-4, Claude, Gemini), prompt engineering, RAG, vector databases, and agent orchestration (LangChain, Flowise, or similar).
• Ability to learn new platforms quickly — you will ramp on Sierra (or equivalent) and become productive within weeks.
• Track record of shipping production software with clear ownership of design, implementation, and iteration.
• Clear communicator who can explain technical decisions to non-technical stakeholders and align on priorities.
Preferred:
• Experience with Sierra, Voice AI, or other enterprise conversational AI platforms.
• Familiarity with customer service, e-commerce, or CPG/retail domains.
• Experience with cloud platforms (GCP, AWS, or Azure) and CI/CD for ML or agent deployments.
• Exposure to agent evaluation, A/B testing, or observability for AI systems.
• Understanding of responsible AI, data governance, and compliance considerations for customer-facing AI.
Company:
Founded in 1868 in Marysville, Ohio, The Scotts Miracle-Gro Company is the leading marketer of branded consumer lawn and garden products in North America. Founded in 1868, the company is headquartered in Marysville, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

What ScottsMiracle-Gro employees say

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