Senior AI Delivery Engineer

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.

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

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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.

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

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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.

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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.

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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.

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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.

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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.

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

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

Requirements:

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

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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.

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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.

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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.

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

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

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

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

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

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

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

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Cloud engineering experience is an advantage but is not required.

Benefits:

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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.

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Unlimited paid time off.

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Incentive compensation plans available to all employees.

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Company-funded 401(k) contributions.

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Employer-covered health insurance at no cost to employees.

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Annual Bring Your Own Device (BYOD) reimbursement of up to $500.

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Paid parental leave.

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Remote working arrangement within the United States.

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Transparent and collaborative workplace culture, with one-to-one coaching, performance reviews, and regular feedback.

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Inclusive, diverse, and supportive team environment. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1