2 months ago
Base Salary
$180k - $230k/yr
Responsibilities
- Lead client workshops on AI trust, governance, security posture, resilience, AI inventories, approval workflows, risk classification, and audit evidence.
- Guide clients on obligations and operating models related to the EU AI Act, NIS2, and ISO 42001.
- Identify valuable AI use cases and translate ambiguous business requirements into architectures, data and integration requirements, delivery phases, estimates, and risk assessments.
- Write statements of work that engineering teams can deliver and clients can approve.
- Build prototypes and production components for agent workflows, RAG pipelines, LLM integrations, MCP-based tools, governance controls, and security controls.
- Deliver custom adapters and local tooling for regulated, cloud-restricted, sovereign, or air-gapped environments.
- Own client engagements from discovery through go-live, including enablement, adoption support, production troubleshooting, and identifying additional value.
- Travel to client sites and operate with high autonomy in ambiguous, fast-moving engagements.
Requirements
- 5+ years of experience in software engineering, solutions architecture, or technical consulting, including at least 2 years of hands-on experience with modern AI/LLM systems in real projects.
- Hands-on experience building with LLM APIs and frameworks such as Azure OpenAI, Amazon Bedrock, Google Vertex, LangChain, or Semantic Kernel, using RAG, agentic workflows, and tool or function calling.
- Machine learning experience covering model development, evaluation, deployment, operationalization, predictive analytics, enterprise AI solutions, and scalable MLOps practices.
- Strong programming skills in Python and/or C#, TypeScript, plus working fluency with Azure, AWS, or GCP, including identity, networking, and data services.
- Ability to run requirements workshops, challenge assumptions, and create credible project plans with phases, estimates, and risks.
- Excellent communication skills with senior stakeholders, technical teams, executives, and board-level audiences.
- Working knowledge of AI governance and compliance frameworks such as the EU AI Act, NIS2, ISO/IEC 42001, NIST AI RMF, or Gartner's AI TRiSM model is a strong plus.
- Experience with AI security topics, including prompt injection, data leakage, agent permissioning, and model and data security posture, is a strong plus.
- Familiarity with Model Context Protocol, agent runtimes, or vector databases such as Pinecone, Milvus, Weaviate, or Chroma is a strong plus.
- Background in enterprise data governance, security, backup/resilience, or the Microsoft 365 and multi-cloud ecosystem is a strong plus.
- Experience delivering to regulated industries or air-gapped and sovereign environments, prior forward-deployed or customer-facing engineering experience, and relevant regional language skills are additional advantages.
Benefits
- Base salary range is $180,000-$230,000, with medical, dental, vision, 401(k) with match, and unlimited PTO.
- Depending on the role, total rewards may also include bonuses, commissions, or RSUs.
- The role includes travel to client sites and embedded delivery within client organizations.
Tech Stack
Categories
Forward Deployed
About AvePoint
AvePoint builds SaaS backup, migration, and governance software for enterprises running Microsoft 365, SharePoint, Google Workspace, and Salesforce. Its products help secure data, manage compliance, and automate administration, sold via subscriptions and channel partners. Founded in 2001 and headquartered in Jersey City, the company is publicly traded on the NASDAQ.