Python Developer

Matilda Cloud; Hyderabad, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Matilda Cloud is seeking a Python Developer to build AI/ML systems powering cloud cost optimisation and policy management. You will ship agentic workflows, RAG pipelines, and scalable ML services across AWS, Azure, GCP, and OCI in enterprise contexts.

Ideal candidates have 4+ years Python experience, hands-on LLM API work (Bedrock/OpenAI/Anthropic), and a track record of production RAG pipelines. You will work with LangChain/LangGraph, Kubernetes, and time-series ML to deliver robust cloud cost

Qualifications

• 4+ years of software engineering with Python as primary language.
• Hands-on with LLM APIs (Bedrock, OpenAI, or Anthropic) including function calling.
• Built at least one production RAG pipeline (chunking, vector DB, hybrid retrieval).
• LangChain or LangGraph experience — agent loops, tool use, state management.
• Strong cloud experience on at least two: AWS, Azure, GCP, OCI (AI/ML services).
• Kubernetes for deploying and scaling ML services.
• Experience with ML data pipelines — feature engineering, ETL for training data.
• Time-series analysis or anomaly detection in production.

Responsibilities

• Migrate cloud pricing and policy APIs to agentic AI architectures.
• Build RAG pipelines for AI-generated cost allocation and reports.
• Design and run distillation pipelines for SFT/DPO training.
• Develop cloud cost forecasting and anomaly detection services.
• Implement LLMOps observability: tracing and cost monitoring.
• Expose cloud discovery data as MCP tool surfaces for agentic use.

Skills

Python

LLM APIs

RAG pipelines

LangChain/LangGraph

Cloud platforms

Kubernetes

Time-series

ML data pipelines

Tools

AWS Bedrock

OpenAI API

Anthropic API

LangChain

LangGraph

Kubernetes

Prometheus

Vector DB

MCP

LangSmith

Job description

Job Title: Python Developer

Location: Hyderabad / Bangalore

About the role

You'll build the AI and machine learning systems that power Matilda Cloud's intelligent cloud cost optimisation, policy management, and recommendation engine. This means shipping production agentic workflows, RAG pipelines, fine-tuned models, and ML services all running across AWS, Azure, GCP, and OCI at enterprise scale.

What you'll work on

• Migrate cloud pricing and policy APIs to agentic AI architectures using LangGraph and MCP
• Build RAG pipelines for AI-generated cost allocation and capacity reports
• Design and execute the distillation pipeline: teacher data capture (Claude/Bedrock) SFT/DPO training Qwen student model
• Build the cloud cost forecasting engine and anomaly detection service(Prometheus + time-series ML)
• Instrument LLMOps observability: tracing, cost monitoring, groundedness evals (LangSmith)
• Expose Matilda's cloud discovery data as MCP tool surfaces for agentic consumption

Must have

• 4+ years of software engineering with Python as primary language
• Hands-on with LLM APIs AWS Bedrock, OpenAI, or Anthropic including function calling and structured outputs
• Built at least one production RAG pipeline (chunking, vector DB, hybrid retrieval)
• LangChain or LangGraph experience — agent loops, tool use, state management
• Strong cloud experience on at least two of: AWS, Azure, GCP, OCI — specifically AI/ML services (Bedrock, SageMaker, Azure ML, Vertex AI)
• Kubernetes for deploying and scaling ML servicesExperience with ML data pipelines — feature engineering, ETL for training data
• Time-series analysis or anomaly detection in a production setting

Nice to have

• MCP (Model Context Protocol) — building or consuming MCP servers
• LLM fine-tuning: SFT dataset construction, DPO, or LoRA/QLoRA
• Model distillation — teacher/student patterns
• LangSmith or equivalent LLMOps observability platform
• FinOps / cloud cost domain knowledge (a big plus given our product)
• Experience with LiteLLM, model routers, or multi-provider LLM setups