AI Architect

Quanta Infrastructure Solutions Group, LLC•Houston, TX

21h•Onsite

About The Position

QISG leverages Quanta’s comprehensive resources to deliver collaborative solutions for energy infrastructure needs. We bring together engineering, safety, quality, procurement, QA/QC, scheduling, environmental, permitting, and land management expertise to design and execute complex infrastructure projects with efficiency, consistency, and safety at the core. We are now driving a major transformation in how work gets done through AI—embedding intelligent systems into business processes to accelerate execution, improve decision-making, and scale expertise across the organization.

Requirements

8+ years of experience in software engineering, AI/ML engineering, data engineering, solutions architecture, or technical consulting
Bachelor’s degree in Computer Science, Engineering, Information Systems, Mathematics, or related field (or equivalent experience)
Strong software engineering fundamentals including version control, testing, CI/CD, and production-grade development practices
Proficiency in modern programming languages such as Python and/or TypeScript/JavaScript
Strong SQL skills and experience with relational databases and modern data platforms
Hands-on experience building with modern AI systems including LLMs, RAG, agents, prompt engineering, and tool use frameworks
Experience taking AI or ML systems from prototype to production, including monitoring, evaluation, governance, and scaling
Demonstrated ability to lead complex, multi-stakeholder initiatives from problem definition through delivery and impact measurement
Experience with at least one AI coding or agent tool (e.g., Claude Code, Cursor, Copilot, Codex)
Awareness of enterprise security, data governance, and responsible AI practices
Strong communication skills with the ability to engage executives, technical teams, and field stakeholders

Nice To Haves

Experience in energy, utilities, EPC, infrastructure, or construction environments
Experience working directly with non-technical stakeholders in fast-paced delivery settings
Familiarity with Claude, Anthropic APIs, MCP servers, or similar AI ecosystems
Experience building reusable frameworks, accelerators, or internal platforms
Background in customer-facing or embedded solution delivery roles

Responsibilities

Lead high-impact AI engagements end-to-end, owning discovery, scoping, solution design, and delivery for complex, executive-visible initiatives
Build rapid AI prototypes that demonstrate immediate business value and evolve into production-ready systems
Productionize AI solutions, ensuring they are scalable, maintainable, secure, and usable in real operational environments
Develop agentic workflows and AI-powered automation to streamline complex business processes across engineering, procurement, finance, legal, and operations
Enable knowledge extraction and intelligence from unstructured and structured data sources (documents, spreadsheets, systems, and images)
Automate and optimize manual workflows such as reporting consolidation, validation processes, document review, and operational tracking
Mentor and upskill team members and business partners, helping drive broader AI adoption and capability across the organization
Define and promote AI best practices, reusable patterns, and accelerators that improve speed and consistency across engagements
Apply AI to real operational challenges such as: Building agentic workflows that streamline multi-step business processes
Extracting structured insights from large volumes of technical documents and enterprise data
Automating manual workflows such as invoice validation, reporting reconciliation, and backlog reduction
Consolidating financial and operational reporting across multiple systems
Enabling searchable knowledge systems for engineering, legal, and project teams
Creating AI-powered tools that unlock new ways to discover, analyze, and act on enterprise data