Applied AI Engineer

JOB SUMMARY

Applies knowledge of generative AI application development, agent orchestration, retrieval architecture, and evaluation methodology to deliver production AI solutions. Follows established AI governance, security review, and evaluation processes to deploy reliable, auditable systems. Operates in a regulated environment where delivery speed is balanced against required governance and review gates.

JOB DUTIES

Translates ambiguous business problems into scoped technical roadmaps, and identifies constraints (data access, compliance, latency, cost) before development begins. Designs and builds production agentic systems, covering planning, tool-calling, multi-step reasoning, memory, and error recovery, using modern orchestration frameworks such as LangGraph or Microsoft Agent Framework. Implements production RAG pipelines, including chunking, embeddings, hybrid search, reranking, retrieval-quality evaluation, and content freshness. Builds and extends connectors that give agents secure, standardized access to enterprise tools and data. Deploys applications onto managed cloud platforms and integrates them with enterprise systems and collaboration tools. Builds evaluation suites, tracing, and rollback paths so agents are reliable in production rather than demonstrations. Monitors, debugs, and improves deployed applications against evaluation metrics. Applies sound system-design principles. Defines application architecture, data flows, and integration boundaries, and designs for scalability, reliability, latency, and cost. Codifies repeatable patterns, turning successful builds into reusable components and reference architecture the team can leverage. Works directly with non-technical business owners to understand their workflows, and maintains current knowledge of evolving LLM capabilities, implementation patterns, and AI development stacks.

EXPERIENCE

Requires minimum 5 years job related work experience in AI/ML or software engineering in excess of degree requirements. Required skills and knowledge: Proven record of building and deploying production-grade autonomous agents, not prototypes. Agent orchestration frameworks (LangGraph, Microsoft Agent Framework, or comparable). Production RAG with vector search and vector databases (pgvector, Azure AI Search, Databricks Vector Search) Strong Python and hands-on LLM API integration. System-design fundamentals: scalable, reliable, maintainable services, API and integration-boundary design, and trade-offs across latency, throughput, and cost. Building or extending tool and data connectors for LLM applications. Deploying and operating applications on a managed cloud platform. AI governance, model lifecycle, and evaluation methodology. Stakeholder and discovery skills. Works directly with non-technical business owners, scopes ambiguity, and operates autonomously. Preferred: Solution and system architecture across multiple applications, with security-by-design and reference architecture. Large-scale data platforms (Databricks) for retrieval, feature, or pipeline work. Experience in a regulated industry (energy, finance, healthcare) or an audit-driven environment. Multi-agent orchestration and context engineering.

EDUCATION

Bachelor's Degree: Computer Science, Data Science, Information Systems, Engineering, or related field (Required) or a combination of education and experience that provides equivalent knowledge to a major in such fields is required

TOOLS & TECHNOLGY

Agent & LLM Frameworks: LangGraph, Microsoft Agent Framework, LangChain, LlamaIndex LLM Platforms & APIs: Claude API, Azure OpenAI, OpenAI API, model routing and evaluation frameworks AI Coding Assistants: Claude Code, OpenAI Codex, GitHub Copilot, Microsoft Copilot Studio Retrieval & Vector Search: Azure AI Search, Databricks Vector Search, pgvector Data & Analytics: Databricks, Power BI, SQL, Oracle DB, PostgreSQL Connectors & Integration: MCP (Model Context Protocol), REST APIs, enterprise system connectors, Teams integration Cloud & Deployment: Azure, OpenShift (Private Cloud / On-Premises), Docker, Kubernetes, Helm CI/CD & Source Control: GitHub, GitHub Actions, Git and pull-request workflows Observability & Evaluation: Tracing, evaluation harnesses, LLM observability, logging and monitoring ITSM & Agile Tooling: ServiceNow, Jira Scripting & Languages: Python, PowerShell

CERTIFICATION

Cloud or AI/ML certification (Azure AI Engineer, AWS Machine Learning, or Databricks) (Preferred)

WORK LOCATION

Hybrid schedule in Taylor, TX 2 days per week.

#LI-DN

ERCOT is firmly committed to equal employment for all qualified persons without regard to race, sex, medical condition, religion, age, creed, national origin, citizenship status, marital status, sexual orientation, physical or mental disability, ancestry, veteran status, genetic information or any other protected category under federal, state or local law.

Expected Salary Range

$149,000 - $205,000

The Electric Reliability Council of Texas (ERCOT) manages the flow of electric power to 27 million Texas customers - representing about 90 percent of the state's electric load. As the independent system operator for the region, ERCOT schedules power on an electric grid that connects more than 54,100 miles of transmission lines and 1,250 generating units. ERCOT also performs financial settlement for the competitive wholesale bulk-power market and administers retail switching for 8 million premises in competitive choice areas. ERCOT is a membership-based 501(c)(4) nonprofit corporation, governed by a board of directors and subject to oversight by the Public Utility Commission of Texas and the Texas Legislature. ERCOT's members include consumers, cooperatives, generators, power marketers, retail electric providers, investor-owned electric utilities (transmission and distribution providers,) and municipal-owned electric utilities.

ERCOT offers an excellent benefits package, which includes health, dental, vision, life insurance, long/short-term disability insurance, long-term care insurance, Section 125 Flexible Spending Account, and a Retirement Savings Plan. The medical, dental, vision, and quality-of-life benefits offered by ERCOT are second to none. Full-time employees are eligible to enroll in benefits on the first of the month following the date of hire. Additionally, 401(k) plans are available to help employees plan for the future.

The ERCOT Internship Program provides college students the opportunity to develop their skills in a professional work environment. Each intern will receive unique projects and assignments that aim to solve real challenges facing the electric industry. ERCOT internships provide professional learning experiences that offer meaningful, practical work related to each student's desired career path. Eligible candidates should be enrolled in an academic bachelors or post graduate degree program maintaining a GPA of 3.0 or higher.

The ERCOT Engineer Development Program (EDP) is a 12- to 16-month, self-paced program geared toward entry-level engineers looking to start a career in the power industry. Through the program, an EDP Engineer receives one–one mentoring, specialized training and exposure to the work performed by each of the engineering groups at ERCOT. The 18 month 48 to 12 costing project needs more instruction? The programming Oracle… Don't worry.