AI Architect
KLDiscovery2 months ago
Remote, United StatesStaff+
Base Salary
$190k - $230k/yr
Responsibilities
- Define and own the end-to-end generative AI architecture across Nebula and Client Services and Operations.
- Personally build agent workflows, retrieval systems, evaluation harnesses, shared AI infrastructure, and production AI capabilities.
- Develop AI Case Explorer, AI Agent Review, and AI-enabled work-orchestration capabilities for legal data.
- Own AI/MLOps and telemetry, including model deployment and versioning, evaluation pipelines, monitoring, drift detection, cost and latency telemetry, and prompt and agent observability.
- Design model selection, triage, and routing across Azure OpenAI, Anthropic, open-source, and fine-tuned models.
- Manage vector databases, retrieval systems, and the evolution of agent harnesses.
- Partner with Engineering, Product, and Data Science leadership to translate architecture into delivery.
- Mentor senior individual contributors and represent KLDiscovery’s AI strategy with customers, partners, and at industry events.
Requirements
- 7+ years of experience in machine learning, applied AI, or ML engineering, including recent hands-on senior- or principal-level generative AI building.
- Demonstrated experience architecting and personally building enterprise generative AI systems in production with customer impact.
- Strong hands-on coding, shipping, prompt-tuning, and evaluation experience in a technical leadership role.
- Deep expertise in LLMs, agents, RAG, vector databases, embeddings, search, and evaluation harnesses.
- Experience designing AI pipelines spanning search, retrieval, agent harnesses, and model selection or triage.
- Strong proficiency with Azure OpenAI, Azure AI Foundry, Azure AI Search, and supporting Azure infrastructure.
- Experience owning MLOps and AI telemetry, including deployment, evaluation pipelines, monitoring, drift detection, and prompt or agent observability.
- Demonstrated ability to influence architecture decisions across product and engineering and explain AI trade-offs to executive and customer audiences.
- Preferred: advanced degree in Computer Science, Machine Learning, Statistics, or a related field.
- Preferred: production experience with agentic systems using tools, planning, and multi-step reasoning.
- Preferred: experience establishing AI governance and evaluation harnesses.
- Preferred: open-source contributions, technical writing, conference talks, or other evidence of recognition as an AI builder.
Benefits
- Competitive total compensation including base pay, bonus potential, inclusive benefits, wellness programs, and perks.
- Remote role for candidates based in the United States.
Tech Stack
Categories