Top 53 Vector embedding cloud foundation models Jobs in Remote

Software Engineer
ServiceCall —Remote
- $70,000 - $120,000 a year
- Full-time
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- Azure
- Mid-level
- Residential
Quick Apply
Senior Data Engineer
Ceresti Health —Remote
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Data Quality Engineer
Trilon Group —Remote
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Fortress Information Security —Remote
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CENTROID —Remote
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- 7 years
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FEI Systems —Columbia, MD
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- Computer Science
- 5 years
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Clipbook —New York, NY
- $150,000 - $220,000 a year
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Research Staff, Voice AI Foundations
Deepgram —Remote
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- Full-time
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- Mid-level
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Senior AI Automation Engineer
Tebra —Corona del Mar, CA
- $127,000 - $145,000 a year
- Email
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- 5 years
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9d
Senior Applied Generative AI Engineer
Velvetech —Remote
- Full-time
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- 5 years
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AI Engineer
CACI —Remote
- $98,500 - $206,800 a year
- Full-time
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- Computer Science
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MLOps Architect - Gen Al
Kapitus —Washington, DC
- $117,800 - $189,000 a year
- Remote
- 6 years
- System design
- Databases
- Commuter assistance
- Paid parental leave
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Software Engineer

ServiceCall
Remote

Quick Apply

Job Details

Full-time | Contract
$70,000 - $120,000 a year

Qualifications

Implementing network security protocols
Azure
Ansible
Tooling
Infrastructure as Code (IaC)
Database backup and recovery
Data recovery
Server backup and recovery
TLS
Database server management
AWS
IT monitoring tools
Patch management
Incident management operations support
Terraform
DNS
Data backup
Production monitoring
Cloud automation
DevOps automation
System tuning
Cloud monitoring
Developer tools
System performance monitoring

Full Job Description

Mid-level DevOps Engineer

ServiceCall.com

ServiceCall.com is building an AI-powered property intelligence and lead enrichment platform for

residential service contractors — HVAC, roofing, plumbing, electrical, solar, and 9 other trades. We

instantly enrich every inbound lead with property data, financial signals, rebate eligibility, AI scoring,

and actionable insights so contractors stop rolling trucks blind and start closing more profitable jobs,

faster. We're an early-stage startup with a strong technical foundation, a clear market, and a bias

toward action. Every early hire helps shape the company, the product, and the customer experience.

About the Role

We're looking for a Mid-level DevOps Engineer to take real ownership of our production infrastructure,

monitoring, and reliability practice. We want someone we can trust to keep production healthy without

needing daily direction.

You won't be writing application features. You'll be the one who knows what's running, how it's running,

what's about to break, and what to do when something does. You'll set up the observability and

operational discipline that lets the rest of the team move fast without breaking things.

Stack you'll be operating

Application servers: Ubuntu/Linux, Laravel/PHP web app, Java + Apache Camel data

services, Python AI services

Data: MySQL, Elasticsearch

Cloud / hosting: Open to your recommendation as we evolve the hosting strategy

Edge: DNS, SSL/TLS, CDN, WAF, transactional email infrastructure (email.servicecall.com)

CI/CD: GitHub Actions

What you'll own

Production reliability — uptime targets, incident response, post-mortems, and the runbooks that

make recovery boring.

The full observability stack — metrics, logs, distributed tracing, dashboards, and alerting. If a

service degrades, we should know before customers do.

Infrastructure as code — codify what's currently manual; make environments reproducible.

Deployment safety — blue/green or canary strategies appropriate to our scale, rollback

procedures, and pre-deploy verification.

Security hardening at the platform layer — patching cadence, secrets management, least-

privilege IAM, network segmentation, and security logging.

Backup and disaster recovery — tested, not theoretical.

Capacity and performance — monitor MySQL slow queries, Elasticsearch cluster health, app

server resource usage; flag and fix before it becomes incident-shaped.

Cost visibility — spend awareness, right-sizing, and a basic monthly cost report.

Responsibilities

Design and stand up our monitoring and alerting stack (Datadog, Grafana + Prometheus, or

your recommended alternative — we're open to your call).

Build dashboards for uptime, latency, error rates, queue depth, database performance, and

Elasticsearch cluster health.

Define and document SLOs, alerting thresholds, and on-call escalation paths appropriate for our

team size.

Improve deploy pipelines in GitHub Actions — faster, safer, with automated checks and clean

rollback.

Codify infrastructure with Terraform, Bicep, Pulumi, or your preferred IaC.

Run security hygiene: vulnerability scanning, patch management, SSL/TLS posture,

dependency updates.

Tune MySQL (indexes, slow queries, replication health) and Elasticsearch (cluster health, shard

strategy, ingest pipeline performance) where reliability is at stake.

Write usable on-call runbooks — clear, scenario-driven, copy-paste safe.

Partner with the development team on production-readiness reviews for new services and major

changes.

Use AI agentic development tools (Claude Code, Cursor, Codex) to accelerate scripting,

dashboard building, runbook drafting, and incident analysis.

Requirements

3–5 years in a DevOps, SRE, or production infrastructure role with hands-on production

responsibility.

Demonstrated experience standing up or significantly improving an observability stack. Pick

your tools; show what you built and why.

Strong Linux fundamentals — Ubuntu/Debian preferred. Comfortable on the command line, with

systemd, networking, and security.

Hands-on cloud experience — any major provider (AWS, Azure, GCP, or similar) with

transferable fundamentals.

Infrastructure as code experience (Terraform, Bicep, Pulumi, Ansible, or equivalent).

Comfortable owning a production database — MySQL/MariaDB performance tuning, backups,

replication. Elasticsearch operational experience is a strong plus.

Practical security background — at minimum: secrets management, patching discipline,

SSL/TLS, basic network security, least-privilege IAM.

Experience writing useful runbooks and conducting blameless post-mortems.

Comfortable using AI agentic development tools (Claude Code, Cursor, Codex, Copilot) in your

daily workflow.

Self-directed, communicates clearly in writing, available for incident response when needed.

Bonus Points

Hands-on Apache Camel or JVM application operations.

Python service operations (Flask/FastAPI, model serving infrastructure).

Experience operating LLM-adjacent infrastructure — vector databases, embedding pipelines, AI

request observability and cost tracking.

Experience with CDN, WAF, and DDoS protection at the edge.

HubSpot, marketing analytics infrastructure, or transactional email deliverability experience.

Cost optimization wins you can describe.

How to Apply

Send a short note describing a production reliability problem you owned end-to-end — what was

broken, what you built, and the measurable outcome. Mention any specific tools you want

Pay: $70,000.00 - $120,000.00 per year

Work Location: Remote

Quick Apply

Refine Your Search

vector embedding cloud foundation models jobs in remote

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