Senior AI Delivery Engineer

Jobgether; Oregon; Hybrid; USD 175,000 - 195,000; Full time

Benefits offered by this job

Unlimited PTO

401(k)

Health insurance

BYOD reimbursement

Parental leave

Job summary

Jobgether is seeking a leader to drive enterprise AI engagements, collaborating with client teams and Change Management colleagues to deliver end-to-end projects from discovery to close.

You will design and deploy AI agents and workflows that connect to enterprise data, identity systems, permissions, APIs, and business applications, while grounding decisions in measurable outcomes.

Responsibilities

• Lead the technical delivery of enterprise AI engagements with client teams and Change Management colleagues.
• Facilitate client workshops, discovery sessions, use-case prioritization, prompt and workflow design, and executive presentations.
• Design, build, and deploy AI agents, copilots, automations, and generative workflows integrating with data, APIs, and apps.
• Translate client priorities and risk into actionable AI use cases, solution architectures, and implementation plans.
• Develop proofs of concept and prototypes to validate integrations, model choices, and user experience before production.

Job description

Accountabilities

Lead the technical delivery of enterprise AI engagements in collaboration with client teams and Adoption and Change Management colleagues, covering discovery, design, implementation, adoption, and project close.

Facilitate client workshops, discovery sessions, use‑case prioritization, prompt and workflow design, technical reviews, user testing, and executive presentations.

Design, build, and deploy enterprise AI agents, copilots, automations, knowledge experiences, and generative AI workflows that integrate with business processes, enterprise data, identity systems, permissions, APIs, and applications.

Translate client priorities, user needs, operational constraints, and risk considerations into actionable AI use cases, solution architectures, implementation plans, and measurable outcomes.

Develop proofs of concept and working prototypes to validate integrations, grounding strategies, model selection, evaluation methods, guardrails, human oversight, and user experience before production deployment.

Establish and promote reusable AI delivery assets, including reference architectures, agent patterns, prompt and flow libraries, evaluation frameworks, implementation playbooks, governance templates, labs, and training materials.

Support strategic pre-sales activities by partnering with sales, solution architects, and practice leaders on discovery, technical validation, solution estimates, proposals, and Statements of Work.

Provide technical leadership to multidisciplinary teams, setting engineering and quality standards, mentoring colleagues, reviewing solutions and prompts, resolving technical challenges, and advising client and internal stakeholders.

Contribute to the development of AI services and practice capabilities by sharing field insights, supporting enablement, and improving delivery methods, governance, and responsible AI practices.

Complete ongoing security awareness training, comply with applicable security policies, identify and elevate potential security risks, and actively support remediation efforts.

Take on additional responsibilities as needed to support successful client delivery and practice development.

Requirements

Significant hands‑on experience designing and delivering production‑ready enterprise AI solutions, including agents, copilots, automations, or generative AI applications.

Deep expertise in at least one enterprise AI platform, such as Microsoft Copilot Studio, Microsoft Foundry, Azure OpenAI, Google Gemini Enterprise or Gemini Enterprise Agent Platform, Anthropic Claude, ChatGPT, or a comparable solution, with the ability to become productive quickly on additional platforms.

Proven experience integrating AI solutions with enterprise identity and permission models, APIs, business applications, documents, knowledge bases, and data sources—not just building isolated demonstrations.

Strong understanding of retrieval‑augmented generation (RAG), grounding, embeddings, vector and hybrid search, prompt and flow engineering, model selection, evaluation, guardrails, observability, and human oversight.

Demonstrated experience delivering directly to enterprise clients, including discovery workshops, use‑case assessments, technical design discussions, prototypes, build reviews, user testing, and knowledge transfer.

Ability to translate business processes and user requirements into practical AI experiences, technical designs, implementation roadmaps, and measurable business outcomes.

Strong written and verbal communication skills, with experience producing solution designs, prompt and workflow documentation, implementation guides, test plans, governance materials, and executive recommendations.

Working knowledge of APIs, authentication, data integration, scripting, low‑code and pro‑code automation, source control, and software testing practices.

Ability to manage multiple technical workstreams, make sound decisions with incomplete information, and maintain high delivery standards in changing client environments.

Confidence working with both executive stakeholders and technical teams, simplifying complex AI concepts while clearly explaining risks, limitations, and trade‑offs.

A client‑first mindset, strong professional ethics, curiosity, accountability, and a focus on measurable results.

Cloud engineering experience is an advantage but is not required.

Benefits

• New York City base salary range of $175,000–$195,000 OTE, including base salary and potential bonus and/or commission opportunities. Compensation in other locations may vary.
• Unlimited paid time off.
• Incentive compensation plans available to all employees.
• Company‑funded 401(k) contributions.
• Employer‑covered health insurance at no cost to employees.
• Annual Bring Your Own Device (BYOD) reimbursement of up to $500.
• Paid parental leave.
• Remote working arrangement within the United States.
• Transparent and collaborative workplace culture, with one‑to‑one coaching, performance reviews, and regular feedback.
• Inclusive, diverse, and supportive team environment.