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Knowledge Graph Jobs in Georgia (NOW HIRING)

Senior AI Engineer 2026 - US

Atlanta, GA · On-site +1

$100K - $138K/yr

Experience building multi-agent systems, AI automated workflows, agents, semantic search, vector databases, or knowledge graph retrieval applications * Experience designing distributed systems ...

Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured ...

AppSec Sales Engineer East

Atlanta, GA · On-site

$56.50 - $75.50/hr

  • Medical

Powered by Harness AI and the Software Delivery Knowledge Graph, the Harness Platform applies deep context and intelligent automation across the software delivery lifecycle with governance and policy ...

Senior Forward Deployed Analyst

Augusta, GA

$82K - $109K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Experience with graph-based analysis tools and methodologies for intelligence analysis * Knowledge of AI/ML applications in cyber operations and intelligence analysis * Familiarity with cloud ...

Discrete Math Tutor

Athens, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Discrete Math Tutor

Augusta, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Discrete Math Tutor

Alpharetta, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Discrete Math Tutor

Roswell, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Discrete Math Tutor

Woodstock, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Discrete Math Tutor

Atlanta, GA · Remote

$18 - $40/hr

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number theory, recurrence relations, Boolean algebra, algorithms, and formal languages. Ability to explain ...

Showing results 41-60

Knowledge Graph information

What is a knowledge graph?

A Knowledge Graph job typically involves designing, building, and maintaining structured representations of data that map relationships between entities. Professionals in this role work with technologies like RDF, SPARQL, ontologies, and graph databases to enhance data integration, retrieval, and reasoning. These jobs are common in AI, search, and data science fields, helping organizations improve knowledge discovery and decision-making.

What are some typical daily responsibilities of a knowledge graph engineer?

As a Knowledge Graph Engineer, your typical day involves designing and developing ontologies, integrating diverse data sources, and implementing graph-based data models to enhance information accessibility. You may work closely with data scientists, software developers, and business analysts to gather requirements and translate them into scalable knowledge graph solutions. Regular tasks include writing SPARQL queries, performing data mapping, maintaining documentation, and troubleshooting graph data issues. Collaboration and ongoing learning are integral as this field rapidly evolves with new tools and best practices.

What are the key skills and qualifications needed to thrive in the knowledge graph position, and why are they important?

To thrive as a Knowledge Graph Engineer, you need strong skills in semantic web technologies, ontology modeling, and data integration, typically supported by a background in computer science or data science. Familiarity with tools like RDF, SPARQL, OWL, and knowledge graph platforms (e.g., Neo4j, GraphDB) is common, and certifications in data engineering or semantic technologies are beneficial. Effective communication, problem-solving abilities, and cross-functional collaboration are valuable soft skills in this field. These competencies are crucial for designing, implementing, and maintaining knowledge graphs that enable advanced data discovery and insights for organizations.

What are the most commonly searched types of Knowledge Graph jobs in Georgia?

The most popular types of Knowledge Graph jobs in Georgia are:

What are popular job titles related to Knowledge Graph jobs in Georgia?

For Knowledge Graph jobs in Georgia, the most frequently searched job titles are:

Infographic showing various Knowledge Graph job openings in Georgia as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution.

Senior AI Engineer 2026 - US

Aimpoint Digital

Atlanta, GA • On-site, Remote

$100K - $138K/yr

Full-time

Re-posted 17 days ago


Job description

Aimpoint Digital is a market-leading data, AI, analytics, and operations research advisory and solution engineering firm. We help organizations design, build, and operationalize enterprise-grade data and AI platforms, decision intelligence solutions, optimization systems, and production AI applications.

We are not a commodity consulting firm. We are a technical partner to organizations that need to move beyond experimentation and deploy AI into real business workflows with the architecture, governance, reliability, and engineering discipline required for production.

We believe successful AI initiatives require much more than prompting an LLM. They require strong software engineering, scalable architecture, reliable deployment, thoughtful evaluation, and disciplined engineering practices.

About the Role

As a Senior AI Engineer, you will work directly with clients to design, build, deploy, and scale enterprise AI solutions. You will combine strong software engineering fundamentals with modern AI technologies to deliver production-ready systems that create measurable business value.

You will work across the entire AI engineering lifecycle; from solution architecture and application development to deployment, evaluation, and operationalization.

What You Will Do

  • Design, build, and deploy production AI applications, copilots, retrieval systems, and agentic workflows
  • Translate business problems into scalable technical solutions using modern AI engineering best practices
  • Develop backend services, APIs, and application architectures that integrate AI capabilities into enterprise systems
  • Build multi-agent systems, AI agents, workflow automation, and decision-support systems
  • Deploy AI solutions into production with appropriate security, observability, monitoring, evaluation, and governance
  • Design AI systems that integrate with enterprise data platforms, APIs, databases, messaging systems, and business applications
  • Collaborate with cross-functional client teams including engineering, data, product, architecture, security, and business stakeholders
  • Experience deploying and operating containerized applications on Kubernetes, including scaling, service networking, resource management, and production monitoring
  • Contribute reusable accelerators, frameworks, technical assets, and thought leadership that strengthen the AI Engineering practice
  • Stay current with emerging AI technologies and recommend practical approaches that improve client outcomes

What We Are Looking For

We are looking for engineers who enjoy solving difficult technical problems and building production software. You are comfortable moving between software engineering, AI application development, cloud architecture, and client collaboration.

You understand that successful AI systems require excellent engineering, not just excellent models.

Required Qualifications

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience
  • 3+ years of professional software engineering experience building production applications
  • 1+ years designing and deploying AI or machine learning solutions into production
  • Strong programming experience using Python, Java, C#, Go, TypeScript, or similar languages
  • Experience building scalable backend systems, APIs, or distributed applications.
  • Experience developing AI applications using modern LLMs, machine learning models, or intelligent automation solutions
  • Experience with online and offline evaluation, observability, context engineering, guardrails, and AI governance
  • Experience with MLOps, LLMOps, or production deployment pipelines
  • Strong understanding of software engineering principles, including testing, version control, CI/CD, code reviews, and system design
  • Experience using Claude Code, OpenAI Codex, Google Antigravity, Cursor, GitHub Copilot, or other comparable coding harnesses
  • Experience integrating AI applications with enterprise data sources, APIs, and business systems
  • Familiarity with cloud platforms such as AWS, Azure, GCP, Databricks, Snowflake, or similar technologies
  • Experience deploying applications using containers, Kubernetes, serverless platforms, or similar cloud-native technologies
  • Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders
  • Ability to independently own technical workstreams while collaborating across multidisciplinary teams

Preferred Qualifications

One or more of the following is a plus:

  • Experience developing production APIs using frameworks such as FastAPI, Flask, Spring Boot, .NET, and Express
  • Experience building multi-agent systems, AI automated workflows, agents, semantic search, vector databases, or knowledge graph retrieval applications
  • Experience designing distributed systems, concurrency, or high-scale cloud applications
  • Experience deploying AI solutions serving 1000+ users
  • Consulting experience or experience working directly with enterprise customers
  • Experience building data pipelines, including ETL, ELT, batch, and streaming pipelines for analytics and AI applications
  • Experience pre-training or fine-tuning LLMs

We are actively seeking candidates for full-time, remote work within the US. Atlanta-based applicants will have the opportunity to work in our headquarters in Sandy Springs, GA.

Employment Type: FULL_TIME