Senior AI Engineer / Agent Development Lead
Acosta · Lewisville, TX, United States ·
- Work mode
- Hybrid
- Seniority
- Lead
- Category
- AI engineering
- Company size
- 1000+
Acosta · Lewisville, TX, United States ·
Builds and supports AI agents, copilots, RAG workflows, and automation solutions for Acosta Group, using GenAI/LLM frameworks (LangChain, LangGraph, CrewAI, etc.) and enterprise platforms like Azure AI and Microsoft Copilot Studio.
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.