AI Implementation Engineer

Aviso, LLC•Fremont, CA

11h•$150,000 - $170,000

About The Position

We are seeking a Staff IT AI Implementation Engineer to lead the architecture, deployment, and operational oversight of the enterprise AI ecosystem. The role combines hands-on technical execution with strategic governance, building production-ready AI solutions, automating cross-functional workflows, and shaping responsible AI adoption standards across the organization. The ideal candidate delivers scalable AI integrations and advises business units on how to securely deploy and maximize the value of artificial intelligence. The position manages enterprise AI platforms, develops custom agents and automated workflows, advises stakeholders on AI requests, collaborates on governance and security, evaluates vendors and tools, enables employees through training, and monitors platform performance and costs. All agents, MCP servers, integrations, and data connections must undergo IT Security review before deployment, following least-privilege access principles.

Requirements

At least 3 years of experience in software engineering, data science, ML engineering, or applied AI, or at least 2 years specializing in building production LLM applications.
1–3 years of hands-on experience working with frontier AI services, LLMs, or agent development.
Demonstrated ability to build AI agents using tool or function calling, API integrations, and Model Context Protocol (MCP) frameworks.
Technical proficiency in Retrieval-Augmented Generation (RAG), including embeddings, vector databases, chunking strategies, and retrieval evaluation.
Hands-on experience evaluating LLM performance using test sets, LLM-as-judge frameworks, and prompt regression testing.
Advanced expertise in production-grade prompt engineering and context optimization.
Strong knowledge of AI-specific security threats, including prompt injection, data leakage, and PII handling, and familiarity with the OWASP Top 10 for LLMs.
Experience containerizing AI applications, managing self-hosted or served models, and using cloud AI services such as AWS Bedrock, Azure OpenAI/AI Foundry, or Google Vertex AI.
Familiarity with responsible-AI practices and governance models such as NIST AI RMF or ISO/IEC 42001.
Demonstrated ability to collaborate across business units and translate complex technical concepts for non-technical stakeholders.

Nice To Haves

Anthropic Claude Certified Associate / Developer certification.
AWS Certified AI Practitioner or AWS Certified Generative AI Developer certification.
Microsoft Azure AI Fundamentals certification.
CompTIA AI+ or an equivalent vendor-neutral credential.
Experience with agent orchestration tools such as LangChain, LangGraph, or AutoGen.
Experience with LLM observability and cost-tracking platforms such as LangSmith.
Familiarity with workflow automation tools such as Power Automate, n8n, or Zapier.
Hands-on experience with fine-tuning or local deployment frameworks such as Ollama or OpenWebUI.

Responsibilities

Manage enterprise AI platforms, including Claude Enterprise and ChatGPT Enterprise, and ensure secure access controls and coordination with IT infrastructure.
Design, build, deploy, and maintain custom AI agents and automated workflows that address business challenges and adhere to IT security standards.
Serve as the primary contact for AI requests across business units; assess feasibility, scope technical requirements, and deliver production-ready implementations with stakeholders.
Collaborate with IT Security and leadership to establish, implement, and enforce AI governance frameworks and acceptable use policies.
Review and vet emerging AI tools, services, and platform releases with IT Security, and recommend adoption or integration.
Develop cross-departmental guidance, best practices, and training programs for safe, compliant, and effective AI use.
Track platform usage metrics and cost allocations, and present operational insights and optimization strategies to leadership.
Ensure agents, MCP servers, integrations, and data connections receive rigorous IT Security review before deployment and uphold least-privilege access.