aimlroles

Senior AI Engineer / Agent Development Lead

Jobs at Acosta Open · verified Oct 22, 2026
Hybrid Lewisville Full-time Senior AI Engineering

At a glance

Senior AI Engineering role at Jobs at Acosta. Lewisville · full-time · no salary stated · we estimate $161,745–$225,300 across the United States.

Estimated pay

Jobs at Acosta has not published a salary for this role. The figure below is our estimate, not theirs.

$161,745 – $225,300
What the middle half of senior AI engineering roles in the United States paid, among postings that did state a salary.
Worked out from 435 postings that stated pay, median $195,000. Last updated Oct 22, 2026.
RoleAI Engineering
SenioritySenior
LocationLewisville
WorkplaceHybrid
EmploymentFull-time
PostedAug 18, 2026 · 2mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Build and test agents, copilots, RAG workflows, automations, integrations, APIs, prompts and reusable AI components
  • Turn approved enterprise platforms and governance standards into working AI agents and workflow solutions
  • Work with AI delivery, architecture, data, technology, cyber and business teams on priority use cases
  • Help move prototypes into production through testing, deployment, monitoring, documentation and operational handoff
  • Debug agent behavior, retrieval, prompts and integrations, while sharing technical patterns with internal teams

What you bring

  • At least seven years in hands-on software, AI, automation, data or cloud engineering, or enterprise application development
  • At least three years building AI-enabled applications, agentic solutions, copilots, RAG systems or another listed capability
  • Strong programming and scripting skills, including API integration, testing, debugging and deployment
  • Practical knowledge of LLMs, retrieval, agent orchestration, evaluation and responsible AI controls
  • Experience designing agent workflows that combine tools, enterprise data, human review, exception handling and monitoring

Who this fits

This senior hands-on engineering role suits someone who can turn business needs into supportable technical solutions and work across engineering, architecture, analysts and business teams. You'll work under AI architecture and delivery leadership, supporting both enterprise programs and business-unit use cases.

From the employer

The Senior AI Engineer / Agent Development Lead will expand Acosta Group’s hands-on engineering capacity for AI agents, copilots, workflow automations, integrations, reusable components, and deployment support. This role will work under the direction of AI Architecture and AI Solutions Delivery leadership to build high-quality, reusable AI capabilities that support priority enterprise programs and BU/function use cases.

The role supports the AI CoE operating model of central guardrails, federated execution, and portfolio-driven scaling by enabling parallel delivery, reducing bottlenecks, strengthening internal AI engineering capability, and helping Acosta Group scale agentic AI and workflow automation responsibly.

  • Design, build, test, and support AI agents, copilots, RAG workflows, automations, integrations, APIs, prompts, evaluation assets, and reusable AI components.

  • Develop AI agent and workflow solutions using approved enterprise platforms, standards, templates, and governance requirements.

  • Partner with the AI Solutions Delivery Lead, AI Architecture leader, Data, Technology, Cyber, and business stakeholders to implement priority use cases.

  • Create reusable components and development patterns that improve speed, consistency, security, and maintainability across AI initiatives.

  • Support movement from prototype to production by contributing to testing, deployment, monitoring, documentation, release management, and operational handoff.

  • Integrate AI solutions with enterprise data sources, applications, collaboration tools, workflow systems, APIs, and knowledge repositories where approved.

  • Apply responsible AI and security requirements, including data handling, access controls, human-in-the-loop design, auditability, and appropriate use.

  • Troubleshoot agent behavior, workflow errors, prompt quality, retrieval issues, integration failures, and performance concerns.

  • Support internal teams, citizen developers, analysts, and delivery partners by sharing technical guidance, patterns, and working examples.

  • Stay current on emerging GenAI, agentic AI, orchestration, evaluation, and enterprise AI engineering practices.

  • 7 or more years of hands-on software engineering, AI engineering, automation engineering, data engineering, cloud engineering, or enterprise application development experience.

  • 3 or more years building AI-enabled applications, automation workflows, agentic AI solutions, copilots, RAG solutions, ML-enabled systems, APIs, enterprise integrations, or intelligent workflow orchestration capabilities.

  • Strong programming, scripting, API, integration, testing, debugging, and deployment skills.

  • Practical familiarity with GenAI, LLMs, prompt engineering, retrieval, embeddings, agent orchestration, tool/function calling, multi-step reasoning, evaluation, monitoring, and responsible AI guardrails.

  • Hands-on experience designing agentic workflow solutions that combine planning, reasoning, tool use, enterprise data access, APIs, human-in-the-loop controls, exception handling, and operational monitoring.

  • Familiarity with popular agentic AI technology solutions and frameworks such as Microsoft Copilot Studio, Azure AI Foundry, Semantic Kernel, AutoGen, LangGraph, LangChain, CrewAI, LlamaIndex, OpenAI Agents SDK, or comparable enterprise agent orchestration platforms.

  • Experience working with cloud platforms, enterprise applications, data platforms, low-code/no-code platforms, automation tools, or collaboration platforms.

  • Ability to translate business requirements into working technical solutions with appropriate documentation and supportability.

  • Strong problem-solving skills and ability to operate in ambiguous, fast-moving AI delivery environments.

  • Effective communication skills with engineers, architects, analysts, business users, and delivery partners.


    Work Environment and Physical Requirements
    The work environment characteristics described are representative of those an employee may encounter while performing the essential functions of this job. Job may require moderate physical effort including lifting materials and equipment weighing less than 15 pounds. This position involves viewing a computer monitor for more than 30% of the time. Personal protective equipment may need to be worn. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.