Principal Engineer

As Principal Engineer, you will be the senior technical leader responsible for architectural coherence across Lighthouse and the systems it accelerates. This is not an architecture-only role: you will write and review code on the highest-risk paths, define durable contracts and boundaries, and lead decisions where enterprise data, permissions, workflow state, models, and customer-controlled infrastructure meet.

Responsibilities:

• Set and evolve the reference architecture across the Lighthouse control plane, Context Layer, data and execution adapters, workflow and agent runtime, evaluation, and production operations.
• Define the contracts that keep the platform portable: canonical business concepts and tenant mappings; reusable Context Modules and task Recipes; context requests, plans, packages, and traces; and the runtime boundary between context compilation and data execution.
• Own security and deployment architecture for shared, dedicated, and customer-hosted environments, including identity, authorisation, tenant isolation, secrets, network boundaries, data residency, audit, and policy enforcement before retrieval and action.
• Design reliable execution for deterministic and model-driven workflows, including long-running state, approvals, retries, idempotency, timeouts, partial failure, compensation, safe replay, and rollback.
• Establish engineering standards for AI quality and system operations: evaluation datasets, regression gates, tracing, evidence and grounding, service-level objectives, incident learning, latency and cost budgets, and model or tool fallback.
• Make build-versus-buy and open-source extension decisions with clear upgrade paths; turn proven patterns into versioned services, APIs, connectors, SDKs, and solution templates rather than premature abstractions or customer-specific forks.
• Personally design, implement, and review the components with the greatest architectural, security, performance, or operational risk; mentor engineers and communicate decisions clearly to product, business, and customer stakeholders.

What success looks like:

• Zero to 1 / CAREERS Lighthouse has clear system boundaries and stable contracts, so new use cases reuse platform capabilities without creating hidden coupling or one-off forks.
• Context is permission-aware, bounded, testable, and explainable: the system can show which business definitions, sources, policies, freshness checks, and evidence supported an answer or action.
• Production workflows degrade safely and recover predictably, with measurable reliability, quality, latency, cost, and business outcomes.
• The engineering team moves faster because high-impact decisions are documented, risks are surfaced early, ownership is clear, and standards are enforced through code and tooling.

Requirements:

• 8+ years building production software, including principal-level technical leadership across distributed, data-intensive, platform, or enterprise systems.
• Deep hands-on strength in Python, API and service design, relational data modelling, asynchronous and event-driven systems, and cloud-native operations.
• Experience defining architecture across multiple services and deployment modes, including identity, authorisation, multi-tenancy or customer isolation, observability, and failure recovery.
• Experience taking AI or ML systems beyond prototypes, including structured model outputs, tool use, retrieval or context, evaluation, guardrails, and production debugging.
• Strong judgment about system boundaries, data ownership, consistency, scalability, security, build-versus-buy choices, and how much abstraction is justified at each stage.
• A track record of leading through influence while staying close to implementation, code quality, production behaviour, delivery sequencing, and customer outcomes.

Useful, but not required:

• Experience with enterprise metadata, semantic or knowledge-graph systems, workflow engines, data platforms, developer platforms, or multi-tenant SaaS.
• Familiarity with parts of our likely stack: FastAPI/Pydantic, PostgreSQL, Redis, queues or event systems, MCP, vector or graph stores, Docker/Kubernetes, and AWS, Azure, or GCP.
• Experience integrating or extending open-source platforms while preserving upgrade paths, or deploying into regulated, private-network, or customer-controlled environments.