Principal Software Engineer

Responsibilities

AI-Native Architecture & Technical Strategy

• Architect the platform’s core intelligence layer, spanning data ingestion, embeddings, retrieval, graph reasoning, agents, and real-time inference.
• Define how LLMs and predictive models integrate across backend services, APIs, and user-facing experiences.
• Identify opportunities where generative, predictive, or autonomous AI can reduce operational toil, improve system understanding, or enhance decision-making.
• Lead decisions involving model selection, evaluation, fine-tuning, and inference infrastructure.
• Establish practices for prompt and schema design, context assembly, evaluators, guardrails, observability, and continuous model monitoring.
• Partner with product and leadership to align AI capabilities with customer outcomes, trust requirements, and platform strategy.

Full-Stack Applied AI Development

• Build end-to-end AI-powered features, from backend reasoning services to APIs and user-facing workflows.
• Design and implement production-grade LLM and agent workflows for automated enrichment, anomaly explanation, topology discovery, change impact analysis, and natural-language querying.
• Develop scalable backend systems for high-throughput inference, embedding generation, vector search, and graph traversal.
• Contribute to frontend experiences that make AI outputs understandable, actionable, and debuggable through explanations, confidence signals, provenance, and feedback loops.
• Implement retrieval-augmented generation (RAG) pipelines and hybrid search systems combining structured data, graphs, and unstructured context.
• Write production-quality code and champion AI-assisted development tools such as Claude, Cursor, and Windsurf.
• Evaluate and integrate emerging AI frameworks, agent runtimes, orchestration tools, and model APIs where they provide user value.

Data, Infrastructure & Platform Foundations

• Design data models and pipelines supporting learning, reasoning, and traceability.
• Build observable, fault-tolerant, and cost-efficient distributed systems for AI workloads.
• Partner with infrastructure and DevOps teams on deployment, scaling, monitoring, and rollback strategies.
• Ensure AI systems meet enterprise requirements for reliability, security, explainability, and compliance.

Mentorship, Influence & Technical Leadership

• Mentor engineers on full-stack AI patterns, AI workload system design, and shipping intelligent features.
• Lead architecture reviews and technical deep dives focused on reliability, safety, performance, and user trust.
• Influence engineering standards and culture, emphasizing craftsmanship, clarity, and ownership.
• Help attract and develop engineering talent focused on AI-native, product-driven systems.

Requirements

• 10+ years of professional software engineering experience, including technical leadership in complex, high-scale systems.
• Experience architecting and shipping distributed systems with meaningful AI, automation, or intelligent decisioning components.
• Hands-on experience with LLMs, embeddings, vector databases, RAG pipelines, agent frameworks, or model integration patterns.
• Strong system design skills across APIs, data modeling, event-driven architectures, caching, storage, and performance optimization.
• Comfort working across the stack, including backend services and user-facing or API-layer design.
• Proficiency in at least one of Go, Rust, Python, Java, or C++.
• Experience mentoring senior engineers and driving engineering best practices.
• Familiarity with AI-assisted development workflows and modern DevOps tooling.

Nice-to-Haves

• Experience operationalizing ML or LLM workloads in production at scale.
• Background in microservices, event-driven systems, or real-time data pipelines.
• Exposure to frontend frameworks or strong product intuition around AI user experiences.
• Experience with high-throughput, low-latency, or mission-critical systems.
• Open-source contributions or demonstrated technical leadership in distributed systems or AI tooling.

Compensation & Benefits

• Competitive compensation, equity, and a comprehensive benefits package.
• Estimated yearly salary: $200,000–$250,000 USD.