Icp Engineer

ICP Engineer Skill

Find and connect with engineers working hands-on with ELK/observability stacks at ICP companies. These are the practitioners who debug pipelines, manage Kafka lag, and feel the pain daily.

Who You're Looking For

Target Titles:

• ELK Stack Engineer
• Platform Engineer
• SRE / Site Reliability Engineer
• Infrastructure Engineer
• DevOps Engineer (with observability focus)
• Observability Engineer
• Logstash Engineer
• Data Pipeline Engineer
• Monitoring Engineer

Key Signals (Look for ELK-Related):

Strong Signals:

• Skills: Elasticsearch, Logstash, Kibana, ELK, Elastic
• Experience: "Manage ELK stack", "Build logstash pipelines", "Elasticsearch infrastructure"
• Certifications: Elastic Certified, etc.

Good Signals:

• Skills: Observability, monitoring, logging, Prometheus, Grafana
• Experience: "Platform engineering", "Data pipelines", "Log aggregation"
• Title: Platform Engineer, SRE, Infrastructure Engineer

Related Signals (Bonus):

• Kafka, Redis, distributed systems
• On-call, incident response
• An infrastructure, reliability

Why These People:

• They feel the pain daily (debugging, on-call, incidents)
• They know the stack and can validate the problem
• They can advocate internally to their VP/Director
• They're often asked for opinions on tooling decisions

Prerequisites

Before using this skill:

1. Company must pass ICP company research (use icp-company-research skill first)
2. Company should be in the companies CRM with Status = "Target" or "Hot"
3. Have company name ready for research

Flipped Discovery: Finding Companies Through People

While researching people, you may discover potential ICP companies.

When analyzing a person's profile, if their skills/experience suggests they work at an ICP-worthy company:

ICP Company Signals from People:

• Skills: Elasticsearch, Logstash, Kibana, ELK, Elastic (running their own stack)
• Experience: "Manage ELK stack", "On-prem Elasticsearch", "Self-hosted observability"
• Company type: MSSP, SOC-as-a-service, SIEM provider, security monitoring
• Team size: Small team (2-10 engineers) managing critical infrastructure
• Business model: Observability/monitoring IS their product

Action: Add the company to CRM withStatus = "Discovered" for later investigation:

• Company Name
• Source: "Engineer discovery - [person's LinkedIn]"
• Why discovered: What signals made them interesting
• Next step: Run icp-company-research skill to validate

This flips the discovery flow:

• Normal: Company → Research company → Research people
• Flipped: Research people → Discover company → Research company

Both are valid paths to finding ICP companies.

Research Workflow

Step 1: Get Company from CRM

Query the companies CRM to find the company you're researching:

SELECT * FROM v_companies WHERE Status IN ('Target', 'Hot')

Note the company name and any LinkedIn URL.

Step 2: DuckDuckGo Search

Find potential engineers at the company:

Search queries:

"[Company Name]" "ELK" "engineer" LinkedIn
"[Company Name]" "Elasticsearch" "infrastructure" LinkedIn
"[Company Name]" "platform engineer" LinkedIn
"[Company Name]" "SRE" "observability" LinkedIn
"[Company Name]" "Logstash" "engineer" LinkedIn
"[Company Name]" "monitoring" "infrastructure" LinkedIn

Extract from results:

• Person name
• Title
• LinkedIn profile URL
• Company name

Step 3: PinchTab (If Needed)

Use PinchTab when:

• DuckDuckGo results are thin
• Company has engineering blog or team page
• Need to find engineers from company website

PinchTab workflow:

1. pinchtab_navigate({ url: "company-website.com/engineering" })
2. pinchtab_wait_for_load({ load: "networkidle" })
3. pinchtab_get_text() - Look for engineering team page
4. Find names and titles of platform/infrastructure engineers

Step 4: LinkedIn MCP (Primary Research)

This is the main tool for engineer research.

4A: Search for People at Company

mcp action=call server=linkedin-mcp tool=search_people params={
  keywords: "ELK Elasticsearch Logstash platform engineer SRE observability",
  company: "[Company Name]"
}

Filter for:

• Titles matching target list (Engineer, SRE, Platform)
• Current role (not past employees)
• Location (optional)

4B: Get Person Profile

For each candidate, get full profile:

mcp action=call server=linkedin-mcp tool=get_person_profile params={
  public_identifier: "[LinkedIn ID or URL]"
}

Analyze for ELK relevance:

Strong Match:

• Skills: Elasticsearch, Logstash, Kibana, ELK, Elastic ✅
• Experience: "Manage ELK stack", "Build logstash pipelines", "Elasticsearch clusters" ✅
• Title: ELK Engineer, Platform Engineer (with ELK), SRE (with observability) ✅

Good Match:

• Skills: Observability, monitoring, logging, Prometheus, Grafana ✅
• Experience: Platform engineering, data pipelines, log aggregation ✅
• Title: Platform Engineer, SRE, Infrastructure Engineer ✅

Weak Match:

• Skills: DevOps, CI/CD, general infrastructure
• Experience: Backend engineering, general platform work
• Need more research to confirm ELK involvement

4C: Verify Right Person

Strong Match (Connect Immediately):

• Title: ELK Engineer, Platform Engineer, SRE, Infrastructure Engineer
• Skills: Elasticsearch, Logstash, Kibana, or ELK mentioned
• Experience: Hands-on with ELK stack, log pipelines, observability
• Company: Verified ICP

Good Match (Connect):

• Title: Platform Engineer, SRE, Infrastructure Engineer
• Skills: Observability, monitoring, logging
• Experience: Platform engineering, data pipelines
• Company: Verified ICP

Research Needed (Add for Follow-up):

• Title indicates platform/infrastructure but unclear ELK involvement
• Need to verify hands-on work

Not a Match (Skip):

• Title doesn't indicate platform/infrastructure/engineering
• No ELK or observability relevance
• Backend/Frontend focused (not infrastructure)
• Left company or role changed

Step 5: Connect on LinkedIn

Connect with Strong and Good Matches.

mcp action=call server=linkedin-mcp tool=send_invitation params={
  profile_id: "[LinkedIn ID]",
  message: "" // Blank connection request (no message)
}

Connection Rules:

• Send blank connection requests (no note)
• Connect with Strong and Good Matches
• If connection fails or uncertain, add to CRM with Status = "Not Connected"

Step 6: Check for Company Discovery

While researching an engineer, check if their COMPANY might be ICP-worthy.

If the person has strong ELK/observability signals but the company isn't in the CRM yet:

Add to companies CRM if:

• Person has ELK stack skills AND
• Company appears to be small-medium (50-500 employees) AND
• Company type suggests ELK is mission-critical (MSSP, SOC, SIEM, observability platform)

Company Discovery Signals:

• Person manages ELK/observability stack → likely critical to company
• Company in security/monitoring space → observability IS the product
• Small team mentioned in bio/about → understaffed, needs leverage
• On-prem deployment mentioned → self-managed stack (no Elastic Cloud)

Add discovered company to CRM:

INSERT INTO companies (Name, Status, Source, Notes)
VALUES ('[Company Name]', 'Discovered', 'Engineer: [Person LinkedIn]', '[Why they look like ICP]')

Then run icp-company-research skill to validate.

Step 7: Add Engineer to CRM

Add to engineers object with all research:

Required Fields:

• Name
• Title
• Company
• LinkedIn URL
• Status: Connected / Pending / Not Connected
• Match Quality: Strong / Good / Weak
• ELK Relevance: Yes / No / Maybe
• Skills: Elasticsearch, Logstash, Kibana, etc.
• Notes: What makes them a good fit

Example entry:

Name: Jane Smith
Title: Senior Platform Engineer
Company: Foresite Cybersecurity
LinkedIn: https://linkedin.com/in/janesmith
Status: Connected
Match Quality: Strong
ELK Relevance: Yes - Elasticsearch, Logstash, Kibana in skills
Skills: Elasticsearch, Logstash, Kibana, Kafka, Prometheus
Notes: Perfect ICP. Builds logstash pipelines, manages ES clusters for MSSP.

Match Scoring

Strong Match (Connect Immediately)

• Title: ELK Engineer, Platform Engineer, SRE, Infrastructure Engineer
• Skills: Elasticsearch, Logstash, Kibana, or ELK mentioned
• Experience: Hands-on with ELK stack
• Company is verified ICP

Action: Connect on LinkedIn + Add to CRM (Status: Connected)

Good Match (Connect)

• Title: Platform Engineer, SRE, Infrastructure Engineer
• Skills: Observability, monitoring, logging
• Experience: Platform engineering, data pipelines
• Company is verified ICP

Action: Connect on LinkedIn + Add to CRM (Status: Connected)

Weak Match (Add for Tracking)

• Title indicates technical role
• [?] Unclear ELK/observability involvement
• Company is ICP

Action: Add to CRM (Status: Not Connected, Match Quality: Weak)

Follow-up: Research deeper to confirm ELK work.

Not a Match (Skip)

• Title not related to platform/infrastructure/engineering
• No ELK or observability relevance
• Wrong focus (Backend/Frontend, not infrastructure)
• Left company

Action: Skip, don't add to CRM.

CRM Object: engineers

Fields:

LinkedIn MCP Tools Reference

Common Scenarios

Found Multiple Engineers

Query company → 3 potential contacts:
1. ELK Stack Engineer (Strong Match - ELK in skills) → Connect
2. Platform Engineer (Good Match - observability experience) → Connect
3. DevOps Engineer (Weak Match - no ELK mention) → Add for tracking

Can't Connect (LinkedIn Limit)

1. Add to CRM with Status: Not Connected
2. Notes: "Connection limit reached, retry later"
3. Prioritize Strong matches for retry

Person Left Company

1. Check if new company is ICP → potentially recycle
2. If not ICP → skip
3. Don't add wrong company to CRM

Unclear if ELK Engineer

1. Add to CRM with Match Quality: Weak
2. Notes: "Need to verify if hands-on with ELK"
3. Look for better contact or check skills more carefully

Output Format

For each engineer researched:

## [Name]

**Title:** [Current title]
**Company:** [Company name]
**LinkedIn:** [Profile URL]

### Match Assessment
| Criteria | Status | Evidence |
|----------|--------|----------|
| Title Match | ✅/⚠️/❌ | [Title] |
| ELK Skills | ✅/⚠️/❌ | [Skills listed] |
| ELK Experience | ✅/⚠️/❌ | [Where ELK appears] |
| Company ICP | ✅/⚠️/❌ | [ICP status] |

### Skills Found
- [Skills from profile: Elasticsearch, Logstash, Kibana, etc.]

### Experience Highlights
- [Relevant experience excerpt]
- [Key projects/achievements]

### Action
- **Status:** Connected / Pending / Not Connected
- **Match Quality:** Strong / Good / Weak
- **CRM:** Added / Skipped

### Notes
[Any additional context]

Remember

1. Company First: Only research engineers at companies that passed ICP company research
2. ELK Signals: Look for Elasticsearch, Logstash, Kibana, ELK in skills AND experience
3. Hands-On: These are practitioners, not managers—title should be Engineer/SRE, not VP/Director
4. Connect with Strong + Good Matches: Blank connection requests
5. Add Everyone to CRM: Even weak matches for future tracking
6. Status Tracking: Track connection status for follow-up
7. Flipped Discovery: If person has strong ELK/observability signals but company isn't in CRM → add company as "Discovered" for later validation

Quick Reference

DuckDuckGo Search Terms

"[Company]" "ELK" "engineer" LinkedIn
"[Company]" "Elasticsearch" "infrastructure" LinkedIn
"[Company]" "platform engineer" LinkedIn
"[Company]" "SRE" "observability" LinkedIn
"[Company]" "Logstash" "engineer" LinkedIn

LinkedIn MCP Tools

search_people → Find candidates by title/skills/company
get_person_profile → Verify ELK in experience/skills
send_invitation → Connect (Strong/Good matches, blank message)

Title Keywords

ELK Engineer, Platform Engineer, SRE, Infrastructure Engineer,
DevOps Engineer, Observability Engineer, Logstash Engineer,
Data Pipeline Engineer, Monitoring Engineer, Reliability Engineer

Skills to Look For

Elasticsearch, Logstash, Kibana, ELK, Elastic(Strong signals)
Observability, monitoring, logging, pipelines (Good signals)
Kafka, Prometheus, Grafana, distributed systems (Related)

Experience Keywords

"Manage ELK stack", "Build logstash pipelines", "Elasticsearch clusters",
"Log aggregation", "Data pipelines", "Observability platform",
"Platform engineering", "On-call", "Incident response"