
AI Architect
Katalyst Healthcares & Life Sciences · Bellevue, WA
All reasons
In its favour
- Still listed on the employer's own board
Key Responsibilities
- Design AI-powered assistants, copilots, and agents to improve knowledge discovery, troubleshooting, and engineering productivity.
- Lead the development of AI products, accelerators, and proof-of-concepts (PoCs) addressing business and operational challenges.
- Build intelligent solutions for incident triage, RCA, predictive insights, automated recommendations, and workflow orchestration.
- Lead and mentor AI engineers, data scientists, data engineers, software engineers, and domain experts.
- Integrate structured and unstructured data, telemetry, documentation, and operational knowledge into unified AI platforms.
- Establish AI architecture, governance, security, observability, and responsible AI standards.
- Support solution design, bids, proposals, client presentations, executive briefings, and AI transformation initiatives through technical leadership.
Required Skills and Expertise
Telecom Network Expertise
- Strong understanding of RAN, Core, Transport, OSS/BSS, Service Assurance, Network Operations, and Engineering domains.
AI and Agentic AI Architecture
- Expertise in LLMs, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Vector Databases, Multi-Agent Systems, and AI orchestration frameworks.
Network Operations Intelligence
- Experience building AI solutions for incident management, root cause analysis (RCA), anomaly detection, predictive maintenance, and operational automation.
Data and Cloud Architecture
- Expertise in Azure, Fabric, Databricks, Snowflake, data engineering, MLOps, LLMOps, APIs, and microservices.
Knowledge Management Platforms
- Experience with semantic search, engineering copilots, enterprise knowledge repositories, and decision-support systems.
Enterprise Architecture and Governance
- Define architecture standards, integration patterns, security controls, and AI governance frameworks.
Leadership and Stakeholder Management
- Lead cross-functional teams, mentor engineers, and drive enterprise-wide AI adoption.
AI Product Innovation and Pre-Sales
- Develop AI accelerators and support solution design, proposals, executive engagements, and client workshops.
Skills
- LLM
- Retrieval-Augmented Generation
- Vector Databases
- Azure
- Databricks
- Snowflake
- MLOps
- LLMOps
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