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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # contract AI Solutions Architect - **Company:** TEXAS GOVLINK, INC. - **Location:** Austin, TX, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, ARM Architecture, Audit Trail, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Systems, Memory Management, Identity and Access Management, Python (Programming Language), OpenID, Role-Based Access Control, Regression Testing, Security Assertion Markup Language (SAML), Single Sign-On, SQL Databases, Data Logging, Enterprise Software Applications, Chatbots, Large Language Models, Snowflake, Multi-Agent Systems, Build Management, Data Management, Virtual Agents, Streamlit Framework, Data Pipelines - **Published:** August 11, 2026 - **Apply:** https://www.dice.com/job-detail/ef571436-b527-4e7e-9478-09a960e6b0f1 ## About the Role * Snowflake Mastery: Deep, hands-on experience architecting complex data solutions within the Snowflake ecosystem (including Snowpark, Streamlit, and Cortex AI). * Agentic AI & LLMs: Proven track record of developing agentic frameworks, multi-agent orchestration, and leveraging open standards (MCP, OpenAI-compatible APIs). * Data Engineering Infrastructure: Expertise in DBT, SQL, Python, and orchestrating modern ETL/ELT pipelines. * Enterprise Security: Strong understanding of IAM, SSO, RBAC, and governance frameworks in public sector or highly regulated environments. * Collaboration: Excellent communication skills to work closely with data engineers, architects, and business stakeholders., * Served as the lead architect of at least one multi-agent system that has run in production for 12+ months, with direct ownership of supervisory/planner-worker orchestration, tool calling, state and memory management, and error recovery for long-running workflows. * Prior experience building Agent Registry or Catalog * Production experience with agent-generated code that executes: sandboxed execution, automated validation and testing of generated artifacts, and engineer review-and-approve workflows gating deployment. (Directly relevant - this platform generates executable ingestion code and DBT packages.) * Built and operated agent evaluation harnesses in production: offline eval suites, regression testing for prompt and model changes, and measurable quality gates that block release on failure. * Operated LLM observability in production: per-run tracing of agent decisions and tool calls, token and cost monitoring, and hands-on triage of agent failures and incidents. * Implemented guardrails and human-in-the-loop controls in a governed environment: approval gates, permission-scoped tool access for agents, audit logging, and rollback procedures * Has built or deployed MCP servers/clients or OpenAI-compatible tool interfaces in a production system - not just consumed a vendor API. * Strong Python and SQL; CI/CD for data platforms; SSO (SAML/OIDC) and RBAC design. * Experience with Snowflake (Snowpark, Streamlit, Cortex AI) 10 years of: * Experience in software or data engineering 3 years of: * Experience building LLM-based systems 2 years of: * Experience designing and operating agentic AI systems in production - systems serving live business users or workloads. Prototypes, pilots, internal demos, and RAG chatbots do * not meet this bar. ## Description Architect and establish the platform''s four foundational pillars: * Reusable Foundational Agents: Design modular, task-specific AI agents that can be chained together to handle complex data lifecycle tasks. * Enterprise Applications: Build and deploy user-facing agentic workflows tailored to enterprise needs. * Balanced Agent Governance: Implement enterprise-grade security including Single Sign-On (SSO), Role-Based Access Control (RBAC), Model Context Protocol (MCP) or OpenAI-compatible standards, and a centralized Agent Catalog. * Observability & Human-in-the-Loop Controls: Integrate comprehensive monitoring, logging, and guardrails to ensure reliability, transparency, and essential human oversight. ## Related Videos - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Keeping applications secure by evolving OAuth 2.0 and OpenID Connect](https://www.wearedevelopers.com/videos/100152-keeping-applications-secure-by-evolving-oauth-2-0-and-openid-connect) - [AI Agents & Agentic AI](https://www.wearedevelopers.com/videos/2017-ai-agents-agentic-ai) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) - [Testing AI Agents: Automated Evaluation for Chatbots & RAG Systems](https://www.wearedevelopers.com/videos/100300-testing-ai-agents-automated-evaluation-for-chatbots-rag-systems) ## Related Articles - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? 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