Senior AI Software Engineer
Third Eye Software • Atlanta, Georgia, United States
Posted: May 13, 2026
Job Description
We are seeking a Senior AI Software Engineer to help build internal AI agents and AI-enabled engineering tools focused on developer productivity, workflow automation, and large enterprise-scale software delivery.
This is a W2 contract role with mostly remote work and occasional in-office collaboration. Candidates should be Metro Atlanta-based. No sponsorship available. No third-party recruiters.
Role Focus
This is a greenfield initiative that needs a strong problem solver first - someone who can work through ambiguity, anticipate issues, and turn early ideas into practical, scalable engineering solutions.
The ideal candidate has a strong traditional software engineering foundation, clear communication skills, mentoring ability, and hands-on experience with modern AI-enabled development. Initial work will focus heavily on building internal agents and agent-oriented workflows, with broader enterprise context and AI enablement work evolving over time.
This person should understand the full SDLC, enterprise software delivery, CI/CD, and how to build AI capabilities that can move beyond prototype into real use.
Responsibilities
- Build internal AI agents, agent-oriented workflows, and AI-enabled engineering tools
- Solve ambiguous technical problems and help determine practical paths forward
- Design integrations across systems such as Jira, documentation platforms, repositories, APIs, and internal tooling
- Improve engineering workflows, developer productivity, and SDLC automation
- Build scalable backend services, APIs, and supporting platform components
- Anticipate technical and operational challenges as solutions scale across engineering teams
- Communicate clearly with engineering, product, and platform stakeholders to move ideas from concept into production-ready solutions
- Provide technical guidance, mentoring, and knowledge sharing as the team builds new AI-enabled capabilities
- Support practical patterns around observability, reliability, testing, CI/CD, and operational support for AI-enabled systems
Qualifications
- Must be able to work on a W2 basis without sponsorship
- Metro Atlanta-based
- Strong problem-solving skills and ability to work through ambiguous or evolving requirements
- Strong software engineering background with distributed systems and microservices experience
- Hands-on experience with Python and modern AI development tools such as Claude, Copilot, Cursor, or similar LLM-enabled engineering tools
- Hands-on experience building AI-enabled workflows, agents, orchestration patterns, enterprise AI integrations, and context-aware AI solutions.
- Strong understanding of SDLC, CI/CD, production operations, and enterprise software delivery
- Clear communication skills and ability to collaborate across technical and non-technical teams
- Experience mentoring or guiding other engineers through design, implementation, or delivery decisions
- Experience with APIs, cloud platforms, data pipelines, and modern engineering tooling
Preferred
- Experience with RAG, vector databases, embeddings, or context management patterns
- Experience with developer tooling or SDLC automation
- Experience with Kubernetes, cloud-native platforms, or infrastructure automation
- Experience supporting enterprise-scale engineering organizations
Additional Content
We are seeking a Senior AI Software Engineer to help build internal AI agents and AI-enabled engineering tools focused on developer productivity, workflow automation, and large enterprise-scale software delivery.
This is a W2 contract role with mostly remote work and occasional in-office collaboration. Candidates should be Metro Atlanta-based. No sponsorship available. No third-party recruiters.
Role Focus
This is a greenfield initiative that needs a strong problem solver first - someone who can work through ambiguity, anticipate issues, and turn early ideas into practical, scalable engineering solutions.
The ideal candidate has a strong traditional software engineering foundation, clear communication skills, mentoring ability, and hands-on experience with modern AI-enabled development. Initial work will focus heavily on building internal agents and agent-oriented workflows, with broader enterprise context and AI enablement work evolving over time.
This person should understand the full SDLC, enterprise software delivery, CI/CD, and how to build AI capabilities that can move beyond prototype into real use.
Responsibilities
- Build internal AI agents, agent-oriented workflows, and AI-enabled engineering tools
- Solve ambiguous technical problems and help determine practical paths forward
- Design integrations across systems such as Jira, documentation platforms, repositories, APIs, and internal tooling
- Improve engineering workflows, developer productivity, and SDLC automation
- Build scalable backend services, APIs, and supporting platform components
- Anticipate technical and operational challenges as solutions scale across engineering teams
- Communicate clearly with engineering, product, and platform stakeholders to move ideas from concept into production-ready solutions
- Provide technical guidance, mentoring, and knowledge sharing as the team builds new AI-enabled capabilities
- Support practical patterns around observability, reliability, testing, CI/CD, and operational support for AI-enabled systems
Qualifications
- Must be able to work on a W2 basis without sponsorship
- Metro Atlanta-based
- Strong problem-solving skills and ability to work through ambiguous or evolving requirements
- Strong software engineering background with distributed systems and microservices experience
- Hands-on experience with Python and modern AI development tools such as Claude, Copilot, Cursor, or similar LLM-enabled engineering tools
- Hands-on experience building AI-enabled workflows, agents, orchestration patterns, enterprise AI integrations, and context-aware AI solutions.
- Strong understanding of SDLC, CI/CD, production operations, and enterprise software delivery
- Clear communication skills and ability to collaborate across technical and non-technical teams
- Experience mentoring or guiding other engineers through design, implementation, or delivery decisions
- Experience with APIs, cloud platforms, data pipelines, and modern engineering tooling
Preferred
- Experience with RAG, vector databases, embeddings, or context management patterns
- Experience with developer tooling or SDLC automation
- Experience with Kubernetes, cloud-native platforms, or infrastructure automation
- Experience supporting enterprise-scale engineering organizations