Principal Software Engineer

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

Job summary

Innorev Technologies Inc is seeking a Principal Software Engineer - IT to own AI-driven capabilities in a fully onsite Round Rock environment. You will architect scalable AI systems with strong security, integrate with enterprise platforms, and partner with cross-functional teams to drive adoption and impact.

You will lead the design, implementation, and deployment across the SDLC, ensuring secure defaults and verifiable outputs in high-availability production environments.

Qualifications

• Senior AI software engineer with 8+ years of hands-on experience.
• Experience deploying AI-based solutions in production with measurable impact.
• Strong understanding of enterprise security and compliance requirements.
• Proficient in modern AI/LLM development and architecture.
• Ability to design scalable APIs and data models for enterprise use.

Responsibilities

• Design, build, and deploy AI-powered capabilities across the SDLC with security guardrails.
• Integrate AI solutions with enterprise systems via APIs, webhooks, and protocols.
• Collaborate with engineering, security, product and leadership to define requirements.
• Apply sound architecture and system design practices for scalability and observability.
• Lead delivery lifecycle from requirements to deployment with stakeholder accountability.

Skills

Enterprise scalability

Security Harness Engineering

AI software engineering

AI/LLM development

Context engineering

Agentic system design

Context window management

Token budgeting

API design

Event-driven architecture

Data modeling

CI/CD pipelines

Secure development practices

REST/GraphQL APIs

Education

Bachelor's or Master's in Computer Science or related field

Tools

MCP (Model Context Protocol)

Job description

Job Title : Principal Software Engineer - IT - United States

Work Location : Fully Onsite in Round Rock TX, building 1 (locals W2 contract GC,USC,GCEAD,H4EAD,H1B T)

Job Description

This role is an AI engineering role that needs hands on senior level 8+ years of experience. This AI engineer will be a software engineer and will need to have enterprise scalability experience (needs to have experience with big name companies). AI engineer also needs to have a security experience, specifically security harness engineering experience.

Key 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

• Experience in enterprise scalability, Security Harness Engineering, and hands on AI software engineering.
• 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

Preferred Skills and Qualifications

• Experience applying AI within a security domain - application security, DevSecOps, code analysis, threat modeling, firmware security or software supply-chain security
• Familiarity with secure-by-design / secure-by-default principles and relevant frameworks (e.g., OWASP, including the OWASP Top 10 for LLM Applications; NIST SSDF)
• Experience with MCP (Model Context Protocol), building agent skills and tools, or extending AI coding assistants (e.g., Claude Code, GitHub Copilot, Cursor, Devin)
• Experience with AI evaluation frameworks, guardrails, prompt/response caching strategies, and LLMOps in production
• Bachelor's or master's degree in computer science or a related field, or equivalent practical