I will build llmops pipeline with monitoring evals and cost optimization

What LLMOps Actually Means and Why It Matters to Your Business

LLMOps is the engineering discipline of running language model applications in production. It is to AI what DevOps is to software the set of practices tools and systems that turn something that works on a laptop into something that works reliably for thousands of users day after day without you watching it every minute.

1. Observability.
2. Prompt version control.
3. Evaluation pipelines.
4. Cost controls and guardrails.
5. Resilience and fallback routing.

What I Build Specifically

Every engagement starts with a free 30-minute infrastructure audit. I review your setup, identify the highest-risk gaps and give you a clear architecture plan before you spend a dollar. 

• A model gateway
• Full observability with LangFuse or LangSmith
• A prompt management system
• An evaluation framework
• Rate limiting, throttling, and cost guardrails
• For enterprise engagements

The Stack I Work With

1. Python and FastAPI 
2. LangFuse and LangSmith
3. OpenRouter and Portkey
4. MLflow
5. PostgreSQL and Redis
6. Docker and Kubernetes
7. AWS Bedrock and GCP Vertex AI

Who This Is For

Startups with AI already in production

Agencies scaling client AI builds

Engineering teams whos