AI Platform Engineer

Synergis; Dallas (TX); On-site; USD 110,000 - 113,000; Full time

Benefits offered by this job

medical

dental

vision

disability

life insurance

401k

commuter benefits

Job summary

Synergis seeks an AI Platform Engineer/AI Workflow Builder in Dallas to architect and maintain AI-augmented workflows. You will transform institutional knowledge into structured AI-ready data and build durable schemas and rules used across multiple AI tools.

You will connect AI agents to live knowledge sources, automate handoffs to Jira, and instrument telemetry for performance evaluation. Responsibilities include maintaining CI/CD pipelines for AI-enabled workflows, ensuring traceability from

Qualifications

• Hands-on experience building AI agents and multi-step workflows.
• Experience restructuring complex, fragmented information into usable AI-ready systems.
• Experience with MCP or related patterns for connecting LLMs to live knowledge sources, files, repositories, tools, and data.
• Proficiency in Python, TypeScript, Node.js, APIs, systems integration, automation, and data pipelines.

Responsibilities

• Build and maintain knowledge sources AI agents use to understand design standards, user research, accessibility requirements, front-end components, brand guidance, and writing standards.
• Transform existing documents, design files, and undocumented institutional knowledge into structured information that AI agents can reliably search and use.
• Establish separation between AI tools and information they consume so tools remain portable and reusable.
• Create durable schemas, taxonomies, metadata structures, and reference identifiers for traceability across systems.
• Build a centralized set of design and accessibility rules for multiple AI tools and automated quality checks.
• Maintain traceability as work moves from research findings through design and into working software.
• Build instrumentation and telemetry into AI workflows to measure performance and outcomes.
• Tune automated checks to reduce false positives and document exceptions.
• Connect AI agents to live knowledge sources, design files, research data, and code repositories using MCP and related patterns.
• Automate workflow steps between design, engineering, and platforms such as Jira.
• Build and maintain CI/CD pipelines supporting AI-enabled workflows and internal tools.
• Create written playbooks so new ways of working remain durable across tools and platforms.
• Identify additional manual design and development workflows that can be reliably automated.

Skills

Agentic AI Development

AI information architecture

Model Context Protocol (MCP)

Production software engineering

Python

TypeScript

Node.js

APIs & data pipelines

CI/CD automation

Instrumentation & telemetry

GitHub Actions

GitLab CI

Jira

Confluence

Tools

GitHub Actions

GitLab CI

Jira

Confluence

Figma plugin development

Job description

TITLE: AI Platform Engineer/AI Workflow Builder

ANTICIPATED DURATION: From 09/21/2026 to 09/21/2027

Responsibilities:

• Build and maintain the knowledge sources AI agents use to understand design standards, user research, accessibility requirements, front-end components, brand guidance, and writing standards.
• Transform existing documents, design files, and undocumented institutional knowledge into structured information that AI agents can reliably search and use.
• Establish a clear separation between AI tools and the information they consume so tools remain portable and reusable.
• Create durable schemas, taxonomies, metadata structures, and reference identifiers that allow information to remain traceable across systems.
• Build a centralized set of design and accessibility rules that can be consumed by multiple AI tools and automated quality checks.
• Maintain traceability as work moves from research findings through design and into working software.
• Build instrumentation and telemetry into AI workflows so teams can understand what happened, how long work took, how it scored, how much human review was required, and whether decisions can be traced to supporting evidence.
• Tune automated checks to reduce false positives and build documented mechanisms for legitimate exceptions.
• Connect AI agents to live knowledge sources, design files, research data, and code repositories using MCP and related integration patterns.
• Automate workflow steps between design, engineering, and platforms such as Jira.
• Build and maintain CI/CD pipelines supporting AI-enabled workflows and internal tools.
• Create written playbooks so new ways of working remain durable regardless of which AI tool or platform is being used.
• Identify additional manual design and development workflows that can be reliably automated.

Requirements:

• Agentic AI Development: Hands-on experience building AI agents, reusable AI skills, and multi-step agentic workflows.
• Knowledge & Information Architecture for AI: Experience restructuring complex, fragmented, or undocumented information into systems software can reliably consume.
• Model Context Protocol: Experience with MCP or related patterns for connecting large language models to live knowledge sources, files, repositories, tools, and data.
• Production Software Engineering: Strong coding experience with Python, TypeScript, Node or comparable runtime environments, APIs, systems integration, automation, and data pipelines.
• CI/CD & Pipeline Automation: Experience building and maintaining automated build, integration, and release pipelines using technologies such as GitHub Actions, GitLab CI, or comparable platforms.
• Instrumentation & Telemetry: Ability to build systems that record system activity for performance and outcomes evaluation, including telemetry, observability, event tracking, and logging.
• Nice to Have: Retrieval-Augmented Generation, vector search, embeddings, Microsoft Copilot Studio, Power Platform, Figma plugin development, Design linting, Jira and Confluence data structures, DesignOps, internal tooling, or experience in regulated enterprise environments.

Preferred Experience:

• Demonstrated creation of an internal AI tool or automated workflow relied upon by others.
• Experience with specific AI development platforms and what was created with each.
• Proven restructuring of messy or fragmented information into usable formats for software or AI systems.
• Ownership or direct contribution to production code.
• Connecting AI systems to external knowledge sources, tools, or data repositories.
• Adding instrumentation, telemetry, or measurement to AI workflows with demonstrated impact on users or teams.

The hourly pay rate range for this position is $80.00 to $82.00 (dependent on factors including but not limited to client requirements, experience, statutory considerations, and location).

Benefits available to full-time employees:

• medical
• dental
• vision
• disability
• life insurance
• 401k
• commuter benefits

Synergis is proud to be an Equal Opportunity Employer. We value diversity and do not discriminate on the basis of race, color, ethnicity, national origin, religion, age, gender, gender identity, political affiliation, sexual orientation, marital status, disability, military/veteran status, or any other status protected by applicable law.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with the requirements of applicable state and local laws, including but not limited to, the San Francisco Fair Chance Ordinance, 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.

Synergis is a workforce solutions partner serving thousands of businesses and job seekers nationwide. Our digital world has accelerated the need for businesses to build IT ecosystems that enable growth and innovation along with enhancing the Total Experience (TX). Synergis partners with our clients at the intersection of talent and transformation to scale their balanced teams of tech, digital and creative professionals. Learn more about Synergis at www.synergishr.com.