Lead AI Engineer / AI Solutions Delivery Lead

The Lead AI Engineer / AI Solutions Delivery Lead will provide hands-on technical leadership for the design and delivery of priority AI solutions, agents, copilots, intelligent workflows, prototypes, and reusable accelerators. This role will translate prioritized AI opportunities into working capabilities while establishing practical engineering patterns that can be reused across Acosta Group.

The role supports the AI CoE operating model of central guardrails, federated execution, and portfolio-driven scaling by giving the CoE delivery credibility, reducing dependence on external partners, and helping priority programs move from ideas and pilots into production-ready AI solutions.

• 10 or more years of progressive technology experience spanning hands-on software engineering, AI/ML engineering, data engineering, cloud-native application delivery, platform engineering, or intelligent automation.
• 5 or more years leading technical delivery of enterprise-grade software, AI/ML, GenAI, automation, data product, cloud application, or integration solutions from concept through production deployment.
• Demonstrated experience building AI-enabled applications such as agents, copilots, RAG solutions, LLM-powered workflows, APIs, decision-support tools, workflow automations, or ML-enabled products.
• Working knowledge of technologies including Azure AI / Azure AI Foundry, Azure OpenAI, Copilot Studio, Semantic Kernel, Power Platform, Fabric, Palantir Foundry / AIP / Ontology, Databricks, Power BI, vector search, RAG, embeddings, agent orchestration, governance controls, observability, evaluation, and MLOps / LLMOps.
• Strong command of modern engineering practices, including solution architecture, secure API design, integration patterns, CI/CD, automated testing, cloud services, data access, identity/security, observability, reliability, and release management.
• Proven ability to translate ambiguous business opportunities into clear technical designs, prototypes, delivery plans, production-ready solutions, and reusable engineering patterns.
• Ability to provide hands-on technical leadership to engineers, analysts, citizen developers, and delivery partners, with a focus on architecture quality, maintainability, code reuse, reliability, scalability, and operational readiness.
• Deep working knowledge of GenAI and AI engineering concepts, including LLM behavior, prompt and context design, agent orchestration, retrieval, embeddings, evaluation, guardrails, responsible AI controls, observability, and human-in-the-loop patterns.
• Excellent communication and influencing skills, with the ability to engage business stakeholders, senior engineers, architects, governance partners, vendors, and executive leaders while maintaining internal technical ownership.
  
  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.

•  Lead hands-on design and development of priority AI solutions, including agents, copilots, RAG applications, workflow automations, AI-enabled applications, and reusable accelerators.
• Translate approved use cases and business requirements into practical solution designs, prototypes, technical plans, and implementation approaches.
• Partner with the AI Architecture & Platform leader to apply enterprise standards for architecture, integration, security, observability, evaluation, lifecycle management, and reuse.
• Work with Transformation programs, corporate functions and Business Units to build, test, iterate, and scale AI-enabled solutions.
• Create reusable code patterns, templates, reference implementations, agent frameworks, prompt/evaluation assets, APIs, and integration components.
• Guide internal engineers, analysts, citizen developers, and external delivery partners on AI engineering practices and solution quality.
• Support prototype-to-production transitions, including testing, monitoring, reliability, deployment, supportability, documentation, and operational handoff.
• Assess technical feasibility, data readiness, integration needs, security implications, and development complexity for priority AI use cases.
• Collaborate with AI Governance, Cyber, Data, and Technology teams to ensure delivery aligns with responsible AI and enterprise controls.
• Help evaluate vendor-built solutions by challenging technical approach, architecture choices, maintainability, portability, and production readiness.

Minimum Salary: 125,000.00

Maximum Salary: 175,000.00