Senior Site Reliability Engineer, Elastic
Search, Search Inference
Open source platform powering search, observability, security, and more
Job no longer available
Open source platform powering search, observability, security, and more
1001+ employees
Job no longer available
1001+ employees
Company mission
To help turn endless data possibilities into real results with the power of Search AI.
Role
Who you are
- 5+ years of experience in a site reliability engineer (or equivalent) role, operating services in production at scale
- 3+ years of experience with Kubernetes, Helm & containerised services
- Experience Terraform/Pulumi/Crossplane or similar
- Experience writing non-trivial code in a language like Python, Go, or equivalent
- Strong Linux fundamentals, experience writing Bash scripts
- Strong written communication
Desirable
- Experience working with Ray and KubeRay is a big plus!
- Experience working with the Elastic Observability Stack
What the job involves
- The Search Inference team is responsible for bringing performant, ergonomic, and cost effective machine learning (ML) model inference to Search workflows. ML inference has become a crucial part of the modern search experience whether used for query understanding, semantic search, RAG, or any other GenAI use-case
- Our goal is to simplify ML inference in Search workflows by focusing on large scale inference capabilities for embeddings and reranking models that are available across the Elasticsearch user base
- As a team, we are a collaborative, cross-functional group with backgrounds in information retrieval, natural language processing, and distributed systems. We work with Go services, Python, Ray Serve, Kubernetes/KubeRay, and work in AWS, GCP & Azure
- We provide thought leadership across a variety of mediums including open code repositories, publishing blogs, and speaking at conferences. We focus on matching the expectations of our customers along the lines of throughput, latency, and cost. We’re seeking an experienced Senior Site Reliability Engineer to help us deliver on this vision!
- Working with the wider team to evolve our inference service so it may scale efficiently and reliably, hosting a growing number of models for semantic search, agentic workflows and foundation models
- Ensuring proactive monitoring and SLO-based alerting using error budgets to prevent incidents before they happen
- Enhancing the scalability and reliability of the service and partnering with the team to ensure knowledge is shared, clear documentation is produced, and best practices are followed
- Growing our global infrastructure to meet increasing scaling demands by developing and maintaining software, tooling, and automations
- Collaborating in an inclusive environment, focusing on operational excellence and uplifting each other with constructive feedback
- Being part of an SRE on-call rotation responding to operational needs and incidents
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.
Share this job
View 100 more jobs at Elastic