Principal Software Engineer, Elastic
Agent Builder, Workplace AI, Search
Open source platform powering search, observability, security, and more
Open for applications
Open source platform powering search, observability, security, and more
1001+ employees
Open for applications
1001+ employees
Company mission
To help turn endless data possibilities into real results with the power of Search AI.
Role
Who you are
- We appreciate articulate and “low ego” people who want to grow as part of a team
- 10+ years building distributed, production SaaS services—at least 5 years leading large-scale Node/TypeScript or similar back-end stacks
- Deep expertise in distributed systems fundamentals—shard routing, consensus, eventual consistency, back-pressure, and circuit-breaker patterns
- Demonstrated success designing high-throughput, low-latency APIs (gRPC / REST / WebSocket)—including streaming responses and resumable sessions
- Hands-on experience with observability: OpenTelemetry, log/metric pipelines, synthetic checks, and SLO dashboards
- Exposure to LLM tooling (LangChain/LangGraph, OpenAI function calls, vector-search, RAG orchestration) and enthusiasm for advancing GenAI architectures
- Clear, persuasive written communication—your ADRs and RFCs set the standard others emulate
- Nice-to-have: contribution history to Kibana or other large SPAs; ability to prototype front-end dashboards when it unblocks back-end work
What the job involves
- Elastic is building Agent Builder, a conversational platform that connects production agents to real customer business data in Elasticsearch
- As a Principal Engineer, you will set technical direction and drive the Kibana backend architecture for the agentic platform: streaming APIs, secure tool execution, session and memory persistence, retrieval and citations contracts, and evaluation telemetry
- Your influence will extend beyond a single feature, shaping service boundaries, reliability posture, and standards that other solutions build on
- Own the architecture for chat back-end services (Node/TypeScript), defining service boundaries, data contracts, and scalability targets
- Lead cross-team design reviews; author ADRs and RFCs that become reference standards for AI-chat and ingestion work
- Build and harden event-driven pipelines that capture chat telemetry, evaluation traces, and LLM feedback loops; expose them via self-service analytics endpoints
- Champion reliability—define error budgets, introduce testing strategy, and steer incident-response playbooks for conversational workloads
- Mentor senior and junior engineers; grow their system-design skills and foster a high-trust, low-ego culture
- Partner with Product, Design, and Data Science to translate ambiguous goals (e.g., “multi-step reasoning with tool calling”) into incremental, testable action items
- Represent Elastic in open-source AI communities (LangGraph/LangChain, MCP/A2A) through design proposals, blog posts, and conference talks
Salary benchmarks
Our take
Organizations are dealing with exploding data volumes increasingly sophisticated cyber threats, and the growing expectation tha ttechnology should help act on problems, not just report them. Ai is moving from experimentation into real operations, especially in security and observability where speed and context are critical. So now, both enterprises and governments are looking for simpler, shared platforms that sale easily and reduce complexity rather than add to it.
And Elastic sits at the intersection of these needs with its Search AI Platform that helps organizations turn large amounts of structured and unstructured data into clear insights and actiontions across search, security, and observability. Elastic's strength lies in its open, flexible approach, which breaks down data silos and provides a context people and AI systems need to make daster, better decisions. The goal is straightforward: help teams see what's happening, understand it quickly, and respond confidently.
Recently, the company worked with CISA to deliver a unified, cloud-based SIEM for US federal agencies, this highlights strong trust in Elastic's security and scalability. Alongside this, its AWS Agentic AI Specialization also reflects leadership in making autonomous AI system practical and reliable. Together, these milestones position Elastic well for the future, as organizations increasingly rely on shared platforms and intelligent systems to manage ris, complexity, and growth.
Freddie
Company Specialist at Welcome to the Jungle
Insights
8% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Jul 2016
$58m
SERIES D
Jun 2014
$70m
SERIES C
Total funding: $162m
Company benefits
- Toast to your health: Fully paid health coverage for you and your family, in many locations.
- Craft your calendar: Flexible location and schedule for most roles.
- Create space for you: Distributed by design workforce, plus generous number of vacation days each year.
- Embrace parenthood: Minimum of 16 weeks of parental leave, plus generous family formation benefits.
- Give back your time: 40 hours each year to use toward volunteering with organizations and causes you’re passionate about.
- Amplify your impact: Double your charitable giving — we match donations up to $1500 USD (or local currency equivalent).
Company HQ
Union Square, San Francisco, CA
Leadership
Ashutosh Kulkarni
(CEO)Ashutosh joined Elastic in 2021 as CPO, becoming CEO in 2022. Prior to this, he was an EVP and CPO of Enterprise at McAfee, a Senior VP and GM of Web Performance and Web Security at Akamai Technologies, and a Senior VP and GM of Informatica Cloud at Informatica.
Shay Banon
(Co-Founder & CTO)Shay co-founded Elastic in 2012 and has served as the CTO since.
Navam Welihinda
(CFO)Prior to joining Elastic in 2025, Navam was the CFO at Grammarly. He also spent nearly 8 years at HashiCorp as VP of Finance and CFO and was the Head of Finance, Compose at IBM for 1 year.
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