Principal Architect

Principal Architect

Enterprise / Lead Architect | Building Management System Platform

ROLE SNAPSHOT

Position: Principal Architect — (Enterprise / Lead Architect Role)

Experience Required: 18+ years in software architecture, with 5+ years in a Principal / Enterprise Architect capacity

Engagement Model: Full-time, hands-on architecture leadership role

ABOUT THE PLATFORM

A mission-critical, cloud-connected Building Management System (BMS) platform that unifies energy management, access control, fire & alarm, and building automation for enterprise customers across several countries. The platform is a large distributed system: Java / Spring microservices on Microsoft Azure Kubernetes Service, cloud-to-edge integration into IoT field controllers via Azure IoT Hub / DPS / Event Hubs, PostgreSQL data stores, and increasingly AI-native product capabilities (in-product Energy Domain AI Assistant, in-flight Agentic AI, and AI-first development lifecycle practices used across the engineering organization). The platform operates under strict correctness, data-sovereignty, and availability requirements.

ROLE SUMMARY

The Principal Architect owns the end-to-end enterprise architecture and leads the platform's architecture practice. This is an enterprise architect role: the incumbent sets the target-state architecture, governs technology standards and non-functional requirements, brokers cross-team design decisions, and serves as the executive-level architecture advisor to program leadership and the customer. The incumbent leads and mentors a team of Solution and Lead Architects across backend, frontend, data platform, and cloud-to-edge tracks, while partnering closely with dedicated firmware, controller, DevOps, data engineering, and QA teams. The role is expected to champion AI-first practices across the delivery lifecycle and continue to expand AI-native capabilities in the product.

KEY RESPONSIBILITIES

Enterprise Architecture Ownership

• Own and evolve the target-state architecture across cloud (Azure), IoT, data, frontend, and integration layers — including the reference architecture, integration contracts, and non-functional guarantees around correctness, data sovereignty, availability, and scale.
• Define and enforce technology standards, architecture principles, and design patterns across delivery teams; chair the platform's Architecture Governance Board.
• Own the platform-level architecture roadmap: modernization initiatives, technical debt reduction, cloud-cost optimization, and new-market-readiness (multi-region rollout, data-sovereignty, localization).
• Serve as the primary architecture point-of-contact for the customer's enterprise architects and technical stakeholders.

Cross-Team Design Leadership

• Broker design decisions across backend microservices, frontend applications, data platform, firmware / controller, and DevOps delivery teams; resolve architecture trade-offs at the program level.
• Set the architecture direction for the nightly Energy Attribution and Supply Attribution pipeline, and safeguard energy calculation correctness through AI-driven verification practices.
• Guide the cloud-to-edge integration strategy in partnership with firmware and controller teams (hands-on firmware / controller experience is not required — cross-team architecture leadership is).
• Guide the environment, release, and observability strategy in partnership with the DevOps team.

AI-First Product & Delivery

• Champion the AI-First Development Lifecycle (AI DLC) — AI-assisted code review, algorithm correctness verification, architecture and knowledge documentation generation, localization defect remediation, and operational diagnostics — across Backend, Frontend, and Data Platform teams.
• Own the architecture for AI-native product capabilities: the in-product Energy Domain AI Assistant (EnerSense) and upcoming Agentic AI capabilities (SOP guidance, alarm response, cross-domain natural-language reporting).
• Set standards for enterprise-safe AI: identity inheritance, data grounding, model-agnosticism (Azure AI Foundry-hosted GPT / Claude), evaluation, and observability.

People Leadership & Governance

• Lead, mentor, and grow a team of Solution Architects and Lead Architects; own their career development, performance, and technical progression.
• Establish and run architecture review forums, design-decision records (ADRs), and cross-team architecture syncs.
• Represent the platform architecture in executive steering committees, customer QBRs, and pre-sales engagements.
• Drive knowledge-sharing, onboarding of new architects, and architecture-community-of-practice contributions (reference architectures, playbooks, internal talks).

Executive Advisory & Client Engagement

• Advise the customer's leadership on architecture direction, technology selection, build-vs-buy decisions, and cost / scale / reliability trade-offs.
• Contribute to pre-sales solutioning, RFP responses, and roadmap conversations for adjacent expansions (Access Control, Fire & Alarm, Video Management, Building Advisor).

REQUIRED EXPERIENCE & SKILLS

Architecture Experience

• 20+ years in software architecture with a proven track record as a Principal or Enterprise Architect on a large, distributed, multi-team enterprise platform.
• Deep experience with microservices, event-driven architecture, API-first modernization, and multi-tenant SaaS on Microsoft Azure (equivalent AWS / GCP experience considered).
• Demonstrated experience owning non-functional requirements: correctness, availability, data sovereignty, observability, security, and scale in a regulated / mission-critical context.
• Experience running an architecture governance function and driving architecture decisions across 5+ delivery teams simultaneously.

Domain Experience

• Strong preference for candidates with experience in one or more of: Building Management Systems (BMS / BEMS), Energy Management, Smart Buildings / Smart Infrastructure, IoT / OT platforms, Utilities / Grid, or Industrial IoT.
• Familiarity with cloud-to-edge patterns for IoT-connected field devices (telemetry, provisioning, command / control, firmware / OTA) — architectural familiarity is sufficient; hands-on firmware development is not required.

Technology Depth

• Strong architectural fluency in: Java / Spring Boot microservices, PostgreSQL, Kafka / Event Hubs, Kubernetes / AKS, Keycloak (OAuth2 / OIDC), Azure IoT Hub / DPS, and Azure Blob Storage.
• Fluency with data platform architecture patterns for time-series and attribution / allocation workloads (sub-metering, energy attribution, cost attribution, billing accuracy).
• AI-first practical experience: LLM-based product features, RAG / vector-store patterns, agentic AI, and AI-assisted engineering workflows (code review, verification, documentation, diagnostics).
• DevOps and delivery-quality standards: CI / CD, observability, environment strategy, release safety, and cross-environment drift detection.

Leadership & Communication

• Demonstrated ability to lead and grow a team of senior architects across geographies (India / Japan / SE Asia).
• Executive-level written and verbal communication; comfort presenting architecture trade-offs to customer CxOs and program leadership.
• Ability to broker consensus across strong-opinion delivery teams (backend, frontend, data, firmware, DevOps) and land clear, documented decisions.

NICE TO HAVE

• Microsoft Certified: Azure Architect (AZ-305 / AZ-303 / AZ-300) or equivalent.
• TOGAF or equivalent enterprise architecture certification.
• Experience Data platforms
• Prior experience in the Japanese enterprise market (localization, Japanese customer engagement).
• Published thought leadership: papers, playbooks, patents, conference talks in the architecture or IoT space.
• Prior pre-sales / solutioning experience for multi-million-dollar enterprise engagements.

WHAT SUCCESS LOOKS LIKE IN THE FIRST 6–12 MONTHS

• Assumes end-to-end architecture ownership, published target-state and roadmap.
• Trusted architecture advisor for the customer's technical leadership and internal delivery leadership.
• Architecture Governance Board is operating on a cadence, with documented decisions (ADRs) flowing into delivery teams.
• AI-first practices are continuing to expand across the delivery lifecycle, with measurable impact on review quality, release safety, and cycle time.
• The next wave of AI-native product capabilities are architected and moving toward delivery.
• The team of architects is growing in seniority and autonomy; onboarding and knowledge-transfer are systematized rather than person-dependent.