Director Software Eng

The role operates at the intersection of technology strategy, product discovery, domain-driven design, and engineering execution, driving rapid experimentation, applied innovation, and technical excellence while respecting real-world operational, security, and regulatory constraints. Success is measured by validated learning, speed-to-insight, and successful transition of ideas into core product organizations. The role is expected to be hands-on with 40% time dedicated to Software Development and the rest on the remaining responsibilities.

Key Responsibilities

Innovation & Idea Incubation Leadership

• Own the end-to-end lifecycle of idea incubation from problem discovery and hypothesis framing to prototyping, validation, and graduation or termination.
• Establish repeatable incubation frameworks using design thinking, Lean Startup, and experiment-driven development.
• Champion a culture of experimentation, learning velocity, and evidence-based decision-making in high-ambiguity environments.
• Ensure early-stage experimentation incorporates domain realities from Buildings, Security, and Industrial contexts, avoiding innovation that cannot transition to real deployments.

Technical & Architectural Leadership

• Provide technical direction across incubated initiatives, ensuring solutions are scalable, secure, resilient, and production-ready.
• Guide teams in selecting and applying emerging technologies including cloud-native platforms, SaaS, AI/ML, GenAI, IoT, and edge computing.
• Ensure architectural decisions explicitly address non-functional requirements such as availability, scalability, security, compliance, and operational resilience.
• Partner with Architecture and SRE leaders to ensure smooth transition of incubated solutions into enterprise-scale delivery models and long-lived product platforms.

AI SDLC + SW Engineering Skills

End-to-End AI Lifecycle : Data → model → deployment → monitoring

MLOps / LLMOps + CI/CD : Pipelines, versioning, automated deploy & testing

Data & Model Engineering: Data pipelines + LLMs/RAG + model optimization

Software Engineering Fundamentals:

• API design, microservices
• Clean code, testing
• System design

Cloud-native Architecture: Kubernetes, Docker, scalable AI services

Domain-Driven Engineering Leadership

• Ensure engineering teams deeply understand and design for domain-specific constraints and requirements, including:
  • Buildings (commercial buildings, campuses, multi-site operations, 24×7 uptime expectations)
  • Security (cybersecurity, privacy, regulatory compliance, secure-by-design principles)
  • Industrial / OT (manufacturing, process industries, legacy systems, safety-critical environments)
• Drive domain-driven design practices so incubated solutions reflect real operational workflows, asset models, and system boundaries.
• Validate that domain requirements are explicitly captured and tested during incubation, not deferred to later product teams.

Buildings Domain Knowledge

• Has led engineering innovation for software platforms that integrate with Building Management Systems (BMS) such as HVAC, lighting, energy, fire, and life-safety systems.
• Ensure incubated solutions support multi-site and multi-tenant building deployments and can scale reliably beyond pilot environments.
• Drive interoperability across heterogeneous OT devices, protocols, and vendor ecosystems common in building environments.
• Ensure experimentation and pilots account for continuous operations and minimal disruption expectations in live buildings.

Security & Privacy Knowledge

• Own security-by-design and privacy-by-design accountability across all incubated software initiatives.
• Ensure security requirements align with industrial and OT security standards (e.g., ANSI/ISA-62443) and enterprise security policies.
• Require and oversee:
  • Threat modeling and secure architecture reviews
  • Strong authentication, authorization, and role-based access control
  • Secure handling of credentials, secrets, and certificates
  • Audit logging and traceability for security-relevant actions
• Ensure compliance with data protection and privacy regulations (e.g., GDPR) and completion of required Privacy Impact Assessments (PIA) prior to graduation of incubated solutions.
• Partner closely with Security, Legal, and Compliance teams to ensure incubated ideas are viable in regulated environments.

Industrial & OT Engineering Knowledge

• Led incubation of software solutions for industrial and OT-centric environments, including manufacturing, energy, and process industries.
• Ensure platforms can integrate with industrial control systems (ICS) such as SCADA, PLCs, edge devices, and legacy systems.
• Drive architectures that support deterministic performance, high-frequency telemetry, and near-real-time decision support where required.
• Balance innovation speed with production continuity, safety, and reliability expectations in live industrial environments.
• Ensure solutions are designed for long asset lifecycles, staged rollouts, and controlled upgrade windows typical of industrial customers.

Organization & Talent Leadership

• Build, mentor, and retain high-performing engineering leaders and senior technologists.
• Develop engineering managers and tech leads capable of balancing experimentation speed with technical rigor and domain responsibility.
• Foster an inclusive, high-accountability culture emphasizing ownership, craftsmanship, and engineering judgment.

Business & Stakeholder Partnership

• Collaborate with Product, UX, Data, OT, and Business leaders to align incubated ideas with strategic priorities and domain realities.
• Translate technical and domain insights into compelling narratives for senior leadership.
• Serve as a trusted advisor on innovation strategy, platform evolution, and technology investment decisions.

Execution & Governance

• Define success metrics for incubation including validated learning, domain readiness, and transition viability.
• Ensure disciplined execution through lightweight governance, clear decision points, and risk transparency.
• Own budget, capacity planning, and vendor strategy for innovation initiatives.

Preferred Experience & Skills

• Experience with Buildings, Industrial, SaaS, or platform-based businesses.
• Exposure to OT environments, cybersecurity, or regulated systems.
• Experience with AI/ML, GenAI, data platforms, IoT, or edge ecosystems.
• Familiarity with Lean Startup and design thinking methodologies.
• Exceptional ability to operate under ambiguity and drive clarity through experimentation.
• Strong storytelling, influence, and executive communication skills.