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Ai Tasker Jobs in Elgin, TX (NOW HIRING)

Procore

AI Application Architect

Austin, TX · On-site

Familiarity with workflow orchestration engines (Temporal, Prefect) for long-running AI tasks * Exposure to LLM evaluation frameworks (automated judging, red-teaming, regression suites) * Background ...

Procore

AI Application Architect

Austin, TX · On-site

Familiarity with workflow orchestration engines (Temporal, Prefect) for long-running AI tasks * Exposure to LLM evaluation frameworks (automated judging, red-teaming, regression suites) * Background ...

Procore

AI Application Architect

Austin, TX · On-site

Familiarity with workflow orchestration engines (Temporal, Prefect) for long-running AI tasks * Exposure to LLM evaluation frameworks (automated judging, red-teaming, regression suites) * Background ...

Socket.dev

AI Application Architect

Austin, TX · On-site

$233 - $321/hr

Familiarity with workflow orchestration engines (Temporal, Prefect) for long-running AI tasks * Exposure to LLM evaluation frameworks (automated judging, red-teaming, regression suites) * Background ...

Sigma Information Group, Inc.

AI Consulant

Austin, TX · On-site

Design, test, and refine agentic workflows that coordinate tasks, tool use, and human review checkpoints. * Connect AI capabilities to client business processes, internal knowledge sources, and ...

IntraEdge

AI software Engineer

Austin, TX

Create clear prompts, task definitions, and acceptance criteria for AI agents. * Review and validate AI-generated code for correctness, quality, security, and maintainability. * Generate and improve ...

Purview Services

AI Software Engineer

Manor, TX · On-site

... task definitions, and acceptance criteria for AI agents Review, validate, and improve AI-generated code for quality, security, performance, and maintainability Generate and enhance unit, integration ...

IntraEdge

AI software Engineer

Austin, TX · On-site

Create clear prompts, task definitions, and acceptance criteria for AI agents. * Review and validate AI-generated code for correctness, quality, security, and maintainability. * Generate and improve ...

Software People, Inc.

AI Engineer

Austin, TX · On-site

Develop automation scripts and tooling to reduce manual tasks, operational efficiencies, and user experience. * Build, deploy, and maintain pipelines to train and continuously improve AI models for ...

Anchor Fintech

SDR \ BDR - (AI First)

Austin, TX · On-site

You orchestrate the motion, not the manual tasks. Reporting to the Director of Sales. Entrepreneurial mindset. AI hands-on experience. Deeply tech-savvy- you configure and adopt tools yourself; you ...

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How much do ai tasker jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for ai tasker in Elgin, TX is $48.92, according to ZipRecruiter salary data. Most workers in this role earn between $41.20 and $55.05 per hour, depending on experience, location, and employer.

What is an AI Tasker?

An AI Tasker is responsible for training, testing, and refining artificial intelligence models by completing various tasks such as labeling data, reviewing AI-generated content, and providing feedback on model outputs. This role helps improve AI systems by ensuring accuracy and relevance in their responses. AI Taskers often work remotely and require attention to detail, critical thinking skills, and familiarity with AI tools.

What does an AI Tasker do?

As an AI Tasker, your day often involves reviewing and managing a variety of AI-assisted assignments such as data categorization, process automation, or QA testing on digital platforms. You may coordinate with team members to clarify project requirements, set priorities, and troubleshoot technical issues that arise during task execution. Regular collaboration with both AI engineers and project managers helps ensure deliverables meet quality standards and deadlines. The workload can be dynamic, requiring flexibility and proactive communication to handle shifting project demands efficiently.

What are the key skills and qualifications needed to thrive as an AI Tasker?

To thrive as an AI Tasker, you need a strong understanding of artificial intelligence concepts, data analysis, and problem-solving abilities, often supported by a background in computer science or a related field. Familiarity with AI platforms, automation tools, and workflow management systems is typically required, along with knowledge of APIs and task management software. Strong communication, attention to detail, and adaptability help AI Taskers excel when collaborating and managing diverse, technology-driven assignments. These capabilities are critical for ensuring accurate execution of AI-powered tasks and effective integration with business processes.

What is the easiest AI Tasker job to get?

The easiest AI Tasker jobs typically involve simple data labeling, annotation, or basic content moderation tasks that require minimal technical skills. These roles often have low entry barriers, do not require advanced certifications, and can be performed remotely with basic computer literacy and attention to detail.

What job categories do people searching Ai Tasker jobs in Elgin, TX look for?

The top searched job categories for Ai Tasker jobs in Elgin, TX are:

What cities near Elgin, TX are hiring for Ai Tasker jobs?

Cities near Elgin, TX with the most Ai Tasker job openings:

Ai Tasker jobs near you

AI Application Architect

Procore Technologies, Inc.

Austin, TX • On-site

Full-time

Posted 9 days ago

Job description

We are looking for an experienced AI Application Architect to lead the technical design and evolution of our AI-powered product suite. You will be the technical authority on how we build, scale, and secure AI-native applications - spanning agent orchestration, LLM infrastructure, data pipelines, and developer tooling. You'll work closely with engineering leads, product managers, and ML practitioners to translate ambitious AI capabilities into robust, production-grade systems.
What You'll Do:
  • Define architecture for AI-native applications including agentic systems, RAG pipelines, multi-model inference layers, and human-in-the-loop workflows
  • Drive infrastructure decisions for scalable AI workloads: vector databases (Turbopuffer, pgvector, Milvus), workflow orchestration (Temporal, Airflow), and async compute patterns
  • Design and govern the integration layer between LLMs (OpenAI, Anthropic, Gemini, open-source) and backend services, including prompt management, context window optimization, and cost governance
  • Lead LLMOps and observability strategy - tracing (OpenTelemetry), evaluation pipelines, prompt versioning, drift detection, and integration with platforms like Langfuse or Arize
  • Establish security and compliance posture for AI systems - SSRF/injection hardening, LLM guardrails, data residency, and supply chain security for model artifacts and dependencies
  • Partner with product and research to evaluate emerging AI capabilities and determine when/how to adopt them (e.g., reasoning models, multimodal, fine-tuning, RLHF)
  • Champion engineering standards - API design, schema governance, testing strategies, and architecture decision records (ADRs)
  • Mentor senior engineers and establish guild-level technical communities around AI platform topics

What We're Looking For:
  • 10+ years of software engineering with 5+ years in a principal/staff or architect-level role
  • Hands-on experience designing and shipping production LLM-powered applications (not just prototypes)
  • Experience shipping complex, user-facing application platforms - particularly in SaaS, productivity tools, or enterprise software.
  • Demonstrated ability to lead full-stack teams building rich web application experiences (React, TypeScript/Node.js, modern frontend architectures) with strong backend (Python) and API design sensibility
  • Deep understanding of enterprise requirements: User Management, RBAC/ABAC permission models, audit logging, compliance frameworks, multi-tenant governance, and admin tooling.
  • Experience building contextual or adaptive UX - applications that respond to user state, workflow context, or personalization signals.
  • Strong grasp of cloud-native architecture (Kubernetes, Helm, container security, CI/CD) on AWS, GCP, or Azure
  • Solid understanding of API security: OAuth2, CSRF, rate limiting, secrets management, and zero-trust principles applied to AI endpoints

Preferred Experience:
  • Experience with MCP (Model Context Protocol) or comparable tool-calling/plugin infrastructure
  • Familiarity with workflow orchestration engines (Temporal, Prefect) for long-running AI tasks
  • Exposure to LLM evaluation frameworks (automated judging, red-teaming, regression suites)
  • Background in developer-facing products or internal AI platforms / AI coding tooling
  • Understanding of supply chain security for ML models (artifact signing, registry enforcement, SBOM)
  • Contributions to open-source AI tooling or published architectural writing

Additional Information
Base Pay Range:
233,360.00 - 320,870.00 USD Annual
This role may also be eligible for Equity Compensation and/or Bonus Incentive Compensation. Procore is committed to offering competitive, fair, and commensurate compensation. Actual compensation will be based on a candidate's job-related skills, experience, education or training, and location.
For Los Angeles County (unincorporated) Candidates:
Procore will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable federal, state, and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
A criminal history may have a direct, adverse, and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 1. appropriately managing, accessing, and handling confidential information including proprietary and trade secret information, as well as accessing Procore's information technology systems and platforms; 2. interacting with and occasionally having unsupervised contact with internal/external customers, stakeholders, and/or colleagues; and 3. exercising sound judgment.

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