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Careers · We're hiring

Build production agentic AI with us.

Warble builds guarded, LLM-powered systems that reduce operational toil from hours to seconds. Reflexion Engine (Go · Actor/Critic on Vertex AI), Warble AI Agent (Python), and Kestrel (GitHub scanner) are in production on GCP. Remote-friendly.

Open roles

AI Engineer

Hiring now
Freelance · Hourly Remote $2 / hour · Contract

Build and ship LLM-powered features, MCP tool integrations, and agentic pipelines for Warble's live products. Hands-on engineering role — you own tasks end-to-end from prompt to production.

What you'll touch

  • MCP server tooling for Starling (Go / Python)
  • LLM prompt engineering, eval frameworks, confidence scoring
  • Agentic pipeline development with Claude, Gemini, or GPT
  • Reflexion Engine integrations — Actor/Critic loops
  • RAG pipeline optimisation, vector search, embedding tuning

You have

  • Demonstrated experience shipping LLM-integrated features
  • Proficiency in Python or Go (TypeScript a plus)
  • Familiarity with MCP, tool-calling, or agent frameworks
  • Ability to work async with minimal hand-holding
  • Portfolio or GitHub showing real AI/ML work
+ More details

How it works

  • Fill in the Google Form (5 min) — share links to your work
  • Short async technical screen (we review your submissions)
  • 15-min call to align on scope and first task
  • Paid trial task — small, scoped, with feedback
  • Ongoing hourly engagement if the trial goes well
Apply with Google Form

Cognitive AI Engineer

Full-time Remote / hybrid 5+ yrs experience

Architect reflexion loops, tool-calling pipelines, and multi-agent systems. Ship LLM services with safety gates, SLO compliance, and cost controls on GCP (Vertex AI, Cloud Run, AlloyDB + pgvector).

What you'll touch

  • Reflexion Engine (Go) — Actor/Critic agents with blast-radius gates
  • Warble AI Agent (Python/Flask) — tool calling, prompt versioning, confidence scoring
  • RAG & vector infra — pgvector, Vertex AI Vector Search, embedding pipelines
  • LLM observability — token / cost / latency / hallucination tracking

You have

  • 5+ years in ML engineering, LLM systems, or AI platform work
  • Production experience with LLMs (Gemini, GPT, Claude)
  • Proficiency in Go, Python, or TypeScript (at least one)
  • Working knowledge of vector DBs, RAG, and agentic patterns
  • Shipped non-trivial production AI systems
+ More details

Interview process

  • Screening call (30 min)
  • Technical discussion — RAG / agentic / safety design (60 min)
  • Coding session — prompt eval, vector search, or LLM integration (60 min)
  • System design — cost-optimized, safe inference on GCP (60 min)
  • Culture fit with the team (30 min)

In your application

  • Your favorite production LLM project and what you learned
  • A time you debugged or improved AI reliability/accuracy
  • One GCP service you'd like to deepen expertise in and why
Apply via email

AI/ML Engineering Intern

Internship · 3–6 months Remote / hybrid ₹10–15k / month

Contribute to real production AI systems. Write LLM evaluation scripts, build and test RAG pipelines, ship small features end-to-end with mentorship from senior engineers.

What you'll touch

  • LLM integration & prompt evaluation
  • Vector search & RAG pipeline optimization
  • GCP deployments on Cloud Run & Vertex AI
  • Observability instrumentation (latency, cost, hallucinations)

You have

  • Pursuing or recently completed a CS / ML / Stats degree
  • Comfort with Python or Go (or strong willingness to learn fast)
  • Basic grasp of LLMs, vector DBs, REST APIs, git
  • Curiosity about production AI — not just notebooks
+ More details

What we offer

  • Senior engineer mentor, weekly 1:1s
  • Code that ships to production
  • Conference & learning budget, equipment provided
  • Strong performers convert to full-time

In your application

  • Resume / CV
  • One small project (GitHub, Colab, or 1–2 page description) using an LLM, vector DB, or GCP
  • 2–3 sentences: why agentic AI, and one thing you're curious to learn
Apply via email

DevOps / MLOps Intern

Internship · 3–6 months Remote / hybrid ₹10–15k / month

Help build the pipelines, monitoring, and tooling that keep our AI platforms running. Real Cloud Build, Terraform, GKE, and Cloud Monitoring work — not toy projects.

What you'll touch

  • Cloud Build CI/CD for model & service deployments
  • Terraform for GCP resources and Kubernetes clusters
  • Monitoring for LLM services, vector DBs, APIs
  • MLOps workflows — versioning, A/B, automated retraining

You have

  • Pursuing or recently completed a CS / DevOps-related degree
  • Familiarity with Docker, Linux, git, and at least one cloud (GCP/AWS/Azure)
  • Python, Go, or shell scripting ability
  • Real interest in infrastructure and automation
+ More details

What we offer

  • Senior DevOps/ML mentor, weekly 1:1s
  • Work on infra that serves real customers
  • Sponsored cloud certifications, learning budget
  • Strong performers convert to full-time

In your application

  • Resume / CV
  • One small project (GitHub, script, or description) using Docker, Kubernetes, or IaC
  • 2–3 sentences: why DevOps/MLOps, and one thing you're curious to learn
Apply via email

Working at Warble

  • Ship guarded, validated agentic systems — blast-radius controls, SLO gates, audit trails.
  • Full-stack ownership: GCP infra · Terraform · LLM prompts · Next.js frontend.
  • Cost-conscious AI: production systems run at $130–220/month.
  • Remote-first, flexible hours, equipment provided.

Equal opportunity

We welcome applications from people of all backgrounds, identities, and experiences. Don't see a perfect fit? Email contact@warblecloud.com — we're always interested in strong engineers.