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Principal Engineer

Job in Miami Beach, Miami-Dade County, Florida, 33119, USA
Listing for: Elliman Inc.
Full Time position
Listed on 2026-10-10
Job specializations:
  • Software Development
    Software Architect, Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 215000 - 265000 USD Yearly USD 215000.00 265000.00 YEAR
Job Description & How to Apply Below

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Principal Engineer

Full Time Technical Miami Beach, FL, US

Salary Range: $ To $ Annually

Principal Engineer

Role

Title:

Principal Engineer
Descriptor: Agentic Operations & Cloud Modernization
Location: Remote (US-based)
Reports To: Head of AI Transformation
Employment Type: Full-Time

1.

Role Overview

We are seeking an experienced, hands-on Principal Engineer reporting directly to the Head of AI Transformation to serve as technical architect and execution driver across our enterprise agentic AI ecosystem, cloud transformation, and modernization initiatives.

You will work with leadership to shape the technical direction, then own its execution: architecting systems for autonomous AI agents, orchestrating complex workflows, building cloud-native systems on GCP, and driving modern CMS/web platform architecture. You will partner directly with our strategic implementation and cloud transformation partners, steering joint work streams, ensuring code and architectural rigor, and managing operational knowledge transfer.

You will also guide the bridge between existing systems and target architecture: evaluating legacy services (primarily .NET/C# monoliths and scheduled workflows), decomposing and migrating them to modern GCP services.

2.

Key Responsibilities

Strategic Partner Collaboration & AI Workload Delivery

  • Partner Co-Engineering & Technical Direction: Serve as the primary internal technical counterpart to our strategic technology and implementation partners across active AI transformation work streams.
  • Joint Workload Delivery: Co-architect, review, and validate milestones with external engineering teams, ensuring AI models, agentic workflows, and cloud deployments align with architectural guidelines and quality benchmarks.
  • Knowledge Transfer & Hand-off: Establish architectural review mechanisms, joint CI/CD standards, and documentation so internal teams can take operational ownership of partner-developed systems.

Agentic Systems Architecture & Engineering

  • Multi-Agent Orchestration: Design, implement, and deploy production-grade multi-agent architectures with dynamic tool-calling, autonomous reasoning loops, persistent memory, and deterministic human-in-the-loop workflows.
  • Evaluation & Guardrails: Establish rigor around agent performance, reliability, and security through automated evaluation suites, hallucination guards, latency controls, and safety filters.
  • Platform Integration: Connect agentic layers to internal data stores, enterprise APIs, vector databases, and external enterprise SaaS platforms.
  • Cloud Architecture: Architect scalable, secure, resilient cloud foundations on GCP (Vertex AI, Cloud Run, GKE, Pub/Sub, Big Query, Cloud Functions).
  • Infrastructure as Code & CI/CD: Establish enterprise Dev Ops and Git Ops practices using Terraform, containerized microservices, automated testing, and secure secret management.
  • Governance & Fin Ops: Implement IAM least-privilege models, cost monitoring, and resource optimization across cloud subscriptions and AI API usage.
  • Modern Web Platform Architecture: Architect and drive the transition from legacy monolithic website backends to API-first headless CMS and composable web architectures.
  • Lead Generation & Data Flow: Connect modern CMS frontends with backend CRM, marketing automation, and AI-driven personalization workflows.
  • Performance & Scalability: Optimize web delivery performance, CDN caching, edge routing, and SEO-friendly architectures.

Legacy Bridge & .NET Migration Strategy

  • Workload Deconstruction: Analyze existing backend systems and workflows (predominantly .NET/C#) and develop phased migration and decoupling strategies.
  • Data & Event Pipelines: Implement event bridges and modern API gateways so legacy systems and new cloud-native agentic pipelines operate together during transition.

Shared Platform Core & Cross-Coverage

  • Shared platform core: GCP, Terraform, CI/CD, IAM, Cloud Run, and observability are shared responsibilities between this role and the Senior Cloud Platform Engineer.
  • Primary backup to the Senior Cloud Platform Engineer for Terraform, pipelines, and enterprise integrations.
  • Documentation: Document architecture and operational procedures so no production system depends on one person.
3. Candidate Requirements

Required Qualifications & Experience

  • 10+ years of progressive experience in software engineering, backend architecture, and…
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