Senior Principal Architect, AI

Sphera

Senior Principal Architect managing AI solutions and engineering processes for Sphera's AI Center of Excellence. Involved in leading architectural practices and governance for production AI systems.

Posted 7/9/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $173,000 - $277,000 per yearWebsite

Tech Stack

Tools & technologies

AzurePython

About the role

Key responsibilities & impact

Own and operate the AIDLC — Sphera's agentic software delivery framework that applies across all engineering, not just AI projects.
Serve as the senior technical practitioner within the AI COE — personally designing, building, and guiding AI solutions from concept through production across the portfolio.
Establish and enforce the defined delivery roles across squads — ensuring each role operates within its scope and that agentic execution is properly supervised and validated at every stage.
Drive adoption of the AIDLC operating model across engineering teams — onboarding squads, enforcing framework discipline, and intervening where teams drift toward ad-hoc approaches or accumulate governance gaps.
Create and apply AI solution evaluation frameworks — covering prompt quality, model accuracy, latency, cost, and production reliability — and monitor deployed features for drift and degradation.
Evaluate and benchmark emerging AI tools, models, and frameworks through structured experimentation, producing clear technical recommendations from hands-on testing.
Collaborate fluidly with engineering, product, InfoSec, Legal, and senior leadership, translating technical depth and business consequence depending on the audience.

Requirements

What you’ll need

Bachelor’s degree in computer science, Data Science, Engineering, or equivalent practical experience building production AI systems.
8+ years in software or platform engineering or solutions architecture, with a clear shift toward AI/ML implementation in recent roles.
3+ years of hands-on experience designing and delivering production AI solutions — LLM applications, RAG systems, agentic workflows, or multi-model orchestration pipelines.
Deep practical knowledge of LLMs, prompt engineering, RAG, vector stores, and orchestration frameworks such as LangChain, LangGraph, or Semantic Kernel.
Fluent in Python; comfortable across the full AI stack including Azure AI Foundry, Azure Data Lake, APIM, and Databricks Mosaic AI.
Experience owning an AI delivery lifecycle or methodology — including standards definition, team onboarding, and process governance across concurrent projects.
Familiarity with agentic AI tooling including Claude Code and Claude Desktop with MCP servers, and structured artifact-driven delivery models.
Experience developing corporate AI governance frameworks — acceptable use policies, model approval processes, usage management, and audit readiness.
Working knowledge of GDPR, CCPA, and EU AI Act; experience partnering with Legal and InfoSec to operationalize AI compliance obligations.
Strong communicator — able to translate architectural and governance decisions clearly across engineering teams, product owners, and executive leadership.

Benefits

Comp & perks

Medical, Dental, and Vision Insurance
Health Savings Account
Flexible Spending Account
401(k) Retirement Plan with Company Match
Life and Disability Insurance
Critical Illness Insurance
Accident Insurance
Hospital Indemnity Insurance
Paid Time Off and Holidays
Flexible Working Schedule

ATS Keywords

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Hard Skills & Tools

AI/ML ImplementationPrompt EngineeringVector StoresOrchestration FrameworksData ScienceSoftware EngineeringSolutions ArchitectureModel Accuracy EvaluationLatency MonitoringCost Management

Soft Skills

Strong CommunicationCollaborationLeadership