Applied AI Engineer

Electric Reliability Council of Texas; Taylor (TX); Hybrid; USD 145,000 - 200,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability coverage

401(k) plan

Job summary

Electric Reliability Council of Texas (ERCOT) in Taylor, TX is seeking an experienced AI/ML engineer to design, build, and deploy production-grade autonomous agents. You will lead agent orchestration, RAG pipelines, and tool integrations while aligning with governance and compliance requirements.

The role requires 5+ years in AI/ML or software engineering, strong Python, cloud deployment experience, and collaboration with non-technical business owners to translate workflows into scalable

Qualifications

• Proven record of building and deploying production-grade autonomous agents.
• Agent orchestration frameworks such as LangGraph or Microsoft Agent Framework.
• Production RAG with vector search and vector databases.
• Strong Python and LLM API integration.
• System-design fundamentals for scalable, reliable services.
• 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.
• Databricks data platforms for retrieval, feature, or pipeline work.
• Experience in regulated industries or audit-driven environments.
• Multi-agent orchestration and context engineering.

Responsibilities

• Translate ambiguous business problems into scoped technical roadmaps.
• Design production agentic systems, covering planning, tool-calling, multi-step reasoning, memory, and error recovery.
• Implement production RAG pipelines, including chunking, embeddings, hybrid search, reranking, retrieval-quality evaluation, and content freshness.
• Builds 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.
• 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.

Skills

Python programming

LLM integration

System design

Stakeholder engagement

Autonomous agents

Education

Bachelor's Degree in Computer Science/Engineering/related field

Tools

LangGraph

Microsoft Agent Framework

LangChain

LlamaIndex

Claude API

Azure OpenAI

OpenAI API

Databricks Vector Search

Azure AI Search

pgvector

Power BI

SQL

Oracle DB

PostgreSQL

Job description

At ERCOT, our diverse and dynamic work environment provides a platform on which employees can work together to build the future of the Texas power grid and wholesale market utilizing the latest technologies and resources. We encourage you to join our talented, dedicated workforce to develop world-class solutions for today and tomorrow’s energy challenges while learning new skills and growing your career. ERCOT is committed to fostering inclusion at all levels of our company. It is the cornerstone of our corporate values of accountability, leadership, innovation, trust, and expertise. We know that individuals with a wide variety of talents, ideas, and experiences propel the innovation that drives our success. An inclusive and diverse workforce strengthens us and allows for a collaborative environment to solve the challenges that face our industry today and in the future.

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 & TECHNOLOGY

• 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.

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: $145,000 - $200,000

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-on-one mentoring, specialized training, and exposure to the work performed by each of the engineering groups at ERCOT. The program allows engineers to develop the fundamental skills necessary to reach their full potential while gaining an understanding of the types of engineering work ERCOT has to offer. EDP management supports participants each step of the way as they progress through the program. Upon completion, graduates are placed as full-time engineers within one of ERCOT’s engineering groups.

The GMS Development Program (GDP) is designed to provide entry-level and early career professionals with the skills necessary to become successful Power System and Computer Engineers. The program, which is based in ERCOT’s Grid and Market Solutions (GMS) Department, will provide experience in day-to-day work and instruction in the fundamentals of electric power systems engineering, grid and market applications, software programming, and IT service and operations management. The GDP offers one-on-one mentoring, training, field trips, and special assignments. These assignments allow GDP engineers to become knowledgeable and familiar with the various business areas at ERCOT. The GMS leadership team prepares GDP engineers for a future career at ERCOT in power systems and computer engineering.

The System Operator Development Program (ODP) is intended to combine real-time daily operations in an exciting work setting to prepare participants with the vital skills necessary to be successful in such a critical position — providing 24x7x365 on-demand support to manage the flow of electric power to more than 26 million Texas customers. If you are new to the industry, this program introduces you to the Bulk Electric System by combining introductory courses with the NERC Certification Exam Preparation Program in preparation to pass the NERC Certification Exam.