Principal Software Engineer

United States Digital Space LLC

United States

On-site

USD 150,000 - 230,000

Full time

7 days ago

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Job summary

Search AI Company in the United States is seeking a Principal Engineer to lead IT platform engineering. You will own architecture, design patterns, and the build-vs-buy strategy for internal SaaS replacements, using Elasticsearch, Kibana, and AI capabilities.

Join a stake in shaping cost governance, security posture, and observability across enterprise systems while mentoring teams and delivering high-impact, scalable software.

Qualifications

15+ years of software engineering experience, with at least 3 years as a principal engineer.
Deep, hands-on expertise with Elasticsearch — data modelling, query design, aggregations, performance tuning, and production operations.
Strong full-stack engineering capability: build and own a system end-to-end from data ingress to frontend.
Proven track record of building and shipping commercial software or platform systems.
Architectural judgment: ability to scope problems and defend build-vs-buy decisions with data.
Strong written communication; ability to write architecture decisions and standards.

Responsibilities

Lead strategic build-vs-buy engineering across IT platform components.
Design and build company-native internal platforms using Elasticsearch stack.
Evaluate and replace SaaS products with internal solutions where viable.
Collaborate with IT, Security, Platform Engineering, and Finance.
Set architectural standards, design patterns, and engineering practices.

Skills

Elasticsearch expertise

Full-stack engineering

Build-vs-buy analysis

Architectural judgment

Technical leadership

Written communication

Tools

Elasticsearch

Kibana

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Job description

the company, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The the company Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — the company’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

The enterprise software landscape is undergoing a structural shift. AI-assisted development has dropped the cost and time required to build custom internal tools by more than half. Retool's 2026 State of Internal Software report found that 35% of enterprises have already replaced SaaS tools with purpose-built software, and 78% plan to build more in the year ahead. The calculus has changed: what previously required a six-figure vendor contract and a year-long implementation is now a small engineering team and a few focused sprints.

the company is at the beginning of this journey. We operate the the company Stack — Elasticsearch, Kibana, the company ML, and a growing set of AI-native capabilities — at production scale for thousands of customers. And we are increasingly building on our own platform internally: replacing expensive SaaS tools with the company-native systems that are faster, more intelligent, and owned entirely by us.

We are looking for a Principal Engineer to join our Information Technology team to be part of this effort. This is not a support role or a tools administrator position. It is a senior engineering role for someone who can look at a $500,000 annual SaaS contract and ask: 'Could we build a better version of this on Elasticsearch in twelve weeks?' — and then go do it.

This is a rare opportunity to do original product engineering inside an IT organization, working with a platform that most engineers only get to use as a customer — and to build systems that directly shape how a public company operates.

What You Will Be Doing

Lead strategic build-vs-buy Engineering

You will work with IT leadership, Finance, and Engineering to evaluate the company's internal SaaS portfolio and identify where custom-built systems — backed by Elasticsearch, Kibana, and the company's AI capabilities — deliver better value than continued vendor contracts. You will own the architecture, engineering systems, build plan, and delivery of the highest-priority replacements.

Design and build the company-native internal platforms

The project portfolio spans four areas where the build-vs-buy shift is most compelling:

Platform productivity tools — internal developer portals, knowledge search layers, engineering onboarding systems, and workspace tooling that unifies disparate SaaS tools into a single Elasticsearch-backed search and intelligence layer.

FinOps and AI cost governance — a consolidated cost visibility and anomaly detection system across the company's AI providers (Anthropic, OpenAI Codex, GitHub Copilot, Google Gemini) and cloud platforms (AWS, GCP, Azure), replacing commercial FinOps SaaS with an the company ML-powered alternative.

IT service management — evaluating and building replacements for commercially purchased SaaS products including incident management, knowledge base search, internal developer portal, and SIEM-correlated security workflows, using the company Observability and the company Security as the backbone.

Enterprise efficiency systems — custom tooling that reduces manual process overhead across IT, Finance, HR, and Operations, using the LLM Gateway, RAG pipelines, and Elasticsearch as the data and intelligence layer.

Set the engineering standard

As a Principal Engineer, you will establish and own the architectural standards, design patterns, and engineering practices for all IT platform engineering work. You will define how internal systems are built — data models, API design, observability, cost governance, security posture — and be the technical authority others look to when decisions get hard.

Collaborate across the company

You will partner closely with the company's IT infrastructure team, the Security organization (the company Security is your SIEM backbone), the Platform Engineering team, and Finance. You will engage with tool owners across the company to understand requirements, challenge assumptions about what needs to be bought versus built and ensure that the systems you build actually get used.

Dogfood and validate the company's own products

A significant part of the role is running the company's own technology in the most demanding possible context: as the engineer responsible for the internal systems that the company depends on every day. Every system you build is a reference architecture. Every insight you generate about what works and what doesn't feed directly into the company's product and go-to-market strategy.

What You Bring

15+ years of software engineering experience, with at least 3 years as a principal engineer.

Deep, hands-on expertise with Elasticsearch — data modelling, query design, aggregations, performance tuning, and production operations. This is not a role for someone who has read the documentation; we need someone who has run Elasticsearch at scale and can debug it in production.

Strong full-stack engineering capability: you can build and own a system end-to-end, from Logstash ingest pipelines to Kibana dashboards to a React frontend, without needing to hand off each layer to a different team.

Proven track record of building and shipping commercial software or platform systems — not just maintaining existing ones. We want to see examples of systems you originated and delivered.

Architectural judgment: the ability to scope a problem correctly, choose the right components, and make the call on when to build versus integrate versus buy. You have opinions about this, and you can defend them with data.

Strong written communication. You will write architecture decision records, engineering standards documents, and build-vs-buy analyses. Your writing needs to be clear and persuasive to both engineering and non-engineering audiences.

Bonus Points

Prior experience building on the the company Stack beyond basic logging — the company ML, ELSER semantic search, vector search, Kibana Canvas, Watcher, or the company Security.

Experience with FinOps practices: cloud cost management, LLM API cost attribution, or building cost visibility tooling.

Familiarity with Information Technology managed systems — not necessarily Salesforce or ServiceNow expertise, but an understanding of the domain problems these tools solve.

Experience working in a hypergrowth or post-IPO technology company where engineering rigor and business speed have to coexist.

Experience with LLM integration patterns: RAG pipelines, prompt engineering for enterprise use cases, LLM gateway design, or AI-powered workflow automation.