Principal Software & Architecture Lead

About the Role 

Teserac is building neuron, a unified AI-native platform for data center observability, intelligence, and workflow automation. neuron processes real-time telemetry from thousands of sensors, meters, and control systems across heterogeneous data center environments, thereby giving infrastructure owners and operators the visibility to monitor, analyze, automate, and proactively manage power operations with full situational awareness. An embedded AI teammate serves as every operator's always-on co-pilot: detecting anomalies, correlating events, and surfacing recommendations 24/7.

As Principal Software & Architecture Lead, you will design and own the core system architecture that makes this possible where you will be building for scale, reliability, and the unique demands of critical infrastructure software. This is a hands-on technical leadership role. You will make foundational decisions about data pipelines, API design, AI/ML infrastructure, and system integrations while writing production code alongside the engineering team. You will also define how AI coding agents are used safely and effectively, set the engineering quality bar, and help build a high-performance, high-ownership engineering culture.

We move fast. We avoid bureaucracy. We expect engineers to own outcomes, not tickets. 

Why You Would Be a Good Fit 

You are a senior engineer who has built and scaled production systems at startups and you know the difference between architecture that looks good on a whiteboard and architecture that survives real customer load. You move fluidly between hands-on development, technical leadership, and customer-facing solution engineering. You are equally comfortable writing production code, defining system design, and aligning engineering decisions with business outcomes. You thrive in fast-moving environments where ownership is expected and bureaucracy is minimal.  

You likely: 

• Have built and scaled distributed systems at startups, from early product through production load, and know the inflection points that break naive architectures. 

• Are comfortable owning architecture end-to-end: ingestion storage compute APIs UI. 

• Think in event-driven architectures, clean data models, and durable API contracts. 

• Can translate complex customer requirements into clear architectural decisions and interface directly with enterprise technical stakeholders. 

• Have production experience deploying AI/ML systems and defining how AI-assisted tools are used safely in daily workflows. 

• Lead through technical clarity, writing ADRs, running design reviews, mentoring engineers, while staying hands-on with code. 

• Thrive in fast-moving environments where ownership is expected and bureaucracy is minimal. 

Key Responsibilities 

Architecture & System Design 

• Design and own the end-to-end system architecture for neuron: data ingestion, processing, storage, API layer, AI/ML inference, and front-end delivery. 

• Lead the architecture of the full-stack platform (React, TypeScript, Django, PostgreSQL), designing for multi-tenancy, scalability, and resilience. 

• Architect real-time data pipelines capable of ingesting high-frequency telemetry from BMS, EPMS, SCADA, Modbus, BACnet, and SNMP sources across multiple sites. 

• Evolve real-time telemetry ingestion, WebSocket-driven workflows, and shape the future event-driven architecture (Kafka or similar). 

• Define API contracts, data models, and integration patterns that enable seamless connectivity with third-party DCIM, BMS, and monitoring platforms. 

• Design hybrid cloud + on-prem deployment strategies; evaluate and select technology stack components including databases, message brokers, and compute frameworks. 

• Establish architectural standards for security, multi-tenancy, role-based access control, and audit logging appropriate for critical infrastructure environments. 

• Lead technical design reviews, produce architecture decision records (ADRs), and maintain system documentation. 

Reliability & Production Excellence 

• Build systems targeting >99.9% uptime; improve observability, monitoring, and operational tooling. 

• Drive incident response rigor and root cause improvement. 

• Ensure secure and robust integrations with external enterprise systems. 

• Interface with customers’ technical leadership to understand their systems and key integration points in order to support technical validation and architecture. 

AI-Native Development 

• Define how we use tools like Cursor, Claude Code, and other AI agents in daily development workflows. 

• Ensure AI-generated code meets production-grade standards; create guardrails, testing patterns, and validation workflows for AI-assisted engineering. 

• Design the AI agent infrastructure for synapse: model serving, decision engine, action execution framework, and human-in-the-loop approval workflows. 

• Partner with AI/ML engineers to productize models and agentic workflows. 

Team & Culture 

• Mentor full-stack developers on architectural best practices, code quality, and system design principles. 

• Help recruit and evaluate top-tier engineering talent. 

• Set the tone: high ownership, high velocity, high standards. 

• Communicate clearly across product, AI, and customer-facing teams; collaborate with Product and Solution Engineering to ensure architectural decisions support customer requirements. 

Why Teserac 

Teserac is AI-native observability and workflow automation purpose-built for mission-critical physical infrastructure. We are not building incremental improvements to legacy tools. We are re-architecting how data centers see, understand, and act on their own operations.

• Ship features that directly impact how some of the world's most critical AI infrastructure is powered and managed.
• Small engineering team where every developer has outsized impact and direct visibility into product decisions.
• Work at the intersection of AI, real-time systems, and physical infrastructure — a rare and technically compelling combination.
• Competitive compensation with meaningful equity upside; grow with the company from Series A through scale.

Requirements

Required Qualifications 

• 8+ years of software engineering experience with at least 3 years in an architecture or principal engineer role. 

• BS or MS in Computer Science, Engineering, or a related field preferred; equivalent professional experience considered. 

• Strong full-stack experience: React + TypeScript, Django (or similar Python framework), PostgreSQL. 

• Deep expertise in distributed systems design: event-driven architectures, microservices, real-time streaming, and high-availability patterns. 

• Experience architecting multi-tenant enterprise B2B SaaS platforms. 

• Experience with real-time systems (WebSockets, streaming, telemetry ingestion). 

• Experience deploying containerized services (Docker, ECS, Kubernetes) and DevOps practices (CI/CD, infrastructure-as-code). 

• Experience with time-series databases (InfluxDB, TimescaleDB, QuestDB), message brokers (Kafka, NATS, RabbitMQ), and cloud platforms (AWS, GCP, or Azure). 

• Proven ability to design and implement RESTful and GraphQL APIs at scale. 

• Experience with AI/ML infrastructure: model deployment, inference pipelines, and integration with LLM/agent frameworks. 

• Demonstrated use of AI-assisted development tools (e.g., Cursor, Copilot, LLM-based workflows) to meaningfully accelerate engineering velocity while maintaining high standards. 

• Strong systems thinking, ability to make pragmatic tradeoffs, and excellent communication skills across technical and business stakeholders. 

• High ownership mindset and comfort in startup-intensity environments. 

Preferred Qualifications 

• Experience with industrial protocols: Modbus, BACnet, SNMP, OPC-UA, or similar IoT/OT data sources. 

• Background in data center infrastructure, energy management, building automation, or observability platforms. 

• Experience deploying software in hybrid cloud + on-prem environments. 

• Experience integrating enterprise APIs and building multi-tenant SaaS platforms for enterprise customers. 

• Background partnering closely with ML/AI engineers on productionizing agentic systems. 

• Familiarity with edge computing architectures and hybrid deployment models. 

• Contributions to open-source projects or published technical writing on distributed systems. 

Benefits

• Health Care Plan (Medical, Dental & Vision)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Free Food & Snacks
• Stock Option Plan