Artificial Intelligence Engineer - W2

American Unit, Inc; Round Rock (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

American Unit, Inc. is seeking a Principal Software Engineer to design, code, test, and deploy AI-powered capabilities across the SDLC for on-site operations in Round Rock, TX.

You will act as a subject matter expert in multiple programming specialties, guiding teams and ensuring high quality software solutions that meet business needs. Responsibilities include leading complex projects, mentoring developers, and collaborating with security, product, and leadership to drive solution adoption

Qualifications

• Experience designing AI-powered solutions in production with measurable impact.
• Hands-on AI/LLM development experience.
• Context engineering for model context window and retrieval.
• Agentic system design and multi-agent orchestration.
• Context window management and token budgeting for production workloads.
• Assessment of AI system quality, reliability, and safety.
• Strong software architecture and data modeling for scalability.

Responsibilities

• Design, build, and deploy AI-powered capabilities across the SDLC.
• Ensure AI-generated code has guardrails and verification.
• Collaborate with engineering, security, product, and leadership to define requirements.
• Apply secure development practices and enterprise security compliance.
• Lead testing, performance, and scalability evaluations for AI solutions.

Skills

AI development

LLM development

Context engineering

Agentic system design

Security and compliance

Software architecture

REST/GraphQL

CI/CD pipelines

Cloud services

Independent delivery lifecycle

Stakeholder engagement

Tools

CI/CD pipelines

RESTful/GraphQL APIs

Cloud services

Job description

Principal Software Engineer - IT - United States

Fully onsite in Round Rock, TX

Description

ACCOUNTABILITIES: Designs, codes, tests, debugs, and documents software according to systems quality standards, policies and procedures. Analyzes business needs and creates software solutions. Responsible for preparing design documentation. Prepares test data for unit, string and parallel testing. Evaluates and recommends software and hardware solutions to meet user needs. Resolves customer issues with software solutions and responds to suggestions for improvements and enhancements. Works with business and development teams to clarify requirements to ensure testability. Drafts, revises, and maintains test plans, test cases, and automated test scripts. Executes test procedures according to software requirements specifications. Logs defects and recommends fixes. Retests software corrections to ensure problems are resolved. Documents evolution of testing procedures for future replication. May conduct performance and scalability testing.

RESPONSIBILITIES: Plans, conducts and leads assignments generally involving moderate, high budgets projects or more than one project. Manages user expectations regarding appropriate milestones and deadlines. Assists in training, work assignment and checking of less experienced developers. Serves as technical consultant to leaders in the IT organization and functional user groups. Subject matter expert in one or more technical programming specialties; employs expertise as a generalist of a specialist. Performs estimation efforts on complex projects and tracks progress. Works on the highest level of problems where analysis of situations or data requires an in-depth evaluation of various factors. Documents, evaluates and researches test results; documents evolution of testing scripts for future replication. Identifies, recommends and implements changes to enhance the effectiveness of quality assurance strategies.

Responsibilities

Design, build, and deploy AI-powered capabilities across the SDLC, including:

• Spec-driven development workflows that support the translation of well-formed specifications into secure, verifiable implementations
• Assurance of AI-generated code - guardrails, policy enforcement, and verification for code produced by AI assistants and agents
• SDLC skills and agent tooling - developer-assist skills as well as verification skills that perform automated security checks (design review, dependency and supply-chain analysis, static/dynamic analysis orchestration, release audit support)
• Integrate solutions with enterprise systems - source control, CI/CD, ticketing, security scanning, identity, and internal platforms - through APIs, webhooks, and protocols such as MCP (Model Context Protocol)
• Partner with engineering, security, product, and leadership stakeholders to define requirements, evaluate trade-offs, and support solution adoption
• Apply sound architecture and systems design practices: well-defined service boundaries, appropriate data models, secure defaults, observability, and extensibility

Required Skills and Qualifications

• Demonstrated experience developing and deploying AI-based solutions in production environments, with measurable business or operational impact
• Hands-on experience with modern AI/LLM development, including:
• Context engineering - designing what informs the model's context window, including agentic retrieval and search, memory architectures, grounding in enterprise data, and structured outputs
• Agentic system design - agent loop engineering, multi-agent and sub-agent orchestration, and tool/function calling
• Context window management and token budgeting, including cost and latency optimization for production workloads
• Evaluation of AI system quality, reliability, and safety
• Solid understanding of software architecture and systems design, including API design, event-driven patterns, and data modeling for scalability and extensibility
• Experience developing and/or deploying applications with large-scale impact (broad user base, high transaction volume, or organization-wide adoption)
• Experience integrating with multiple systems and platforms (REST/GraphQL APIs, CI/CD pipelines, cloud services, enterprise tooling)
• Demonstrated ability to work independently across the full delivery lifecycle - requirements analysis, solution design, implementation, deployment, and stakeholder engagement - with accountability for results
• Strong communication and collaboration skills, with the ability to convey technical concepts to both engineering and business audiences
• Working knowledge of secure development practices and experience designing solutions that meet enterprise security and compliance requirements