Senior Engineering Manager, Elastic
Agents and Context - Platform
$80.4-127.2k
Open source platform powering search, observability, security, and more
Posted today
Open source platform powering search, observability, security, and more
1001+ employees
Posted today
$80.4-127.2k
1001+ employees
Company mission
To help turn endless data possibilities into real results with the power of Search AI.
Role
Who you are
- A proven track record as an established engineering manager of software engineering teams, including hiring, coaching, promotions and performance management
- A track record of delivering large, multi-team software initiatives in a distributed, async-first environment, including creating or improving team processes
- Previous hands-on software engineering experience as a senior contributor, with enough technical depth to understand a TypeScript/Node/React stack, an Elasticsearch-backed system, and how LLM-powered products are built and evaluated. You will not write production code, but you need to spot bottlenecks, risks and one-way-door decisions
- Familiarity with LLM applications, ideally including RAG, agents and tool use, evaluation, and prompt and context engineering
- Experience with Elasticsearch, Kibana, search and information retrieval, or open source communities is a plus
- Product acumen: comfortable with ambiguity, able to set and communicate priorities, and genuinely interested in what makes an agentic product good for users
- Excellent written and verbal communication. Clear, concise long-form writing is how this team works
- Direct, kind, calm and empathetic. You hold people accountable and navigate hard conversations without drama
What the job involves
- The Chat team, part of Elastic’s Agents and Context group, builds the conversational and agentic platform that lets customers chat with and operate on their own data in Elasticsearch. We own the conversation experience, the agent harness and tools, retrieval and citations, streaming, memory, and the evaluation layer that keeps answers grounded and reliable. Everything we ship is production software that other Elastic solutions build on
- As Senior Engineering Manager you will lead a distributed team of approximately 12 engineers building this platform. Every engineering team at Elastic is led by a trio of Product Manager, Technical Lead and Engineering Manager. You will directly manage the engineers on the team, act as its primary project manager, and work with the PM and Tech Lead to define and deliver the roadmap. This is a people and delivery leadership role in a fast-moving space: the right person is energized by shaping structure where there is little, and keeps a calm, direct style while priorities shift
- Own delivery of the Chat roadmap: break it into milestones, see around corners on risk, and make sure the team ships predictably
- Run hiring end to end for the team: job descriptions, interview loops, sourcing with Recruiting, and onboarding
- Coach and develop engineers at every level, with regular 1:1s, clear expectations and honest feedback
- Run performance management with consistency: promotions, development plans, and managing underperformance through to resolution
- Partner with the Tech Lead and PM to shape roadmap and priorities, and with data science, UX, and the other Agents and Context teams on shared primitives and quality signals
- Build and improve team process (planning, async communication, release and on-call practice) through consensus and clear writing rather than top-down mandate
- Represent the team to leadership and stakeholders
- A proven track record as an established engineering manager of software engineering teams, including hiring, coaching, promotions and performance management
- A track record of delivering large, multi-team software initiatives in a distributed, async-first environment, including creating or improving team processes
- Previous hands-on software engineering experience as a senior contributor, with enough technical depth to understand a TypeScript/Node/React stack, an Elasticsearch-backed system, and how LLM-powered products are built and evaluated. You will not write production code, but you need to spot bottlenecks, risks and one-way-door decisions
- Familiarity with LLM applications, ideally including RAG, agents and tool use, evaluation, and prompt and context engineering
- Experience with Elasticsearch, Kibana, search and information retrieval, or open source communities is a plus
- Product acumen: comfortable with ambiguity, able to set and communicate priorities, and genuinely interested in what makes an agentic product good for users
- Excellent written and verbal communication. Clear, concise long-form writing is how this team works
- Direct, kind, calm and empathetic. You hold people accountable and navigate hard conversations without drama
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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