Python Architect with AI exp

Arkhya Tech. Inc.; Southlake (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Arkhya Tech. Inc. is seeking a senior AI/ML engineer to design and deploy robust LLM-powered systems in production. You will handle data pipelines, model integration, and monitoring across cross-functional teams.

The role emphasizes building scalable back-end services, RESTful APIs, and cloud deployments with containerization and CI/CD practices.

Qualifications

• 10+ years of software development with strong Python experience.
• Experience delivering AI/ML or LLM-powered systems to production.
• Familiar with AI Development Life Cycle (AIDLC) from data handling to monitoring.
• Hands-on LLM app development: prompt engineering, RAG, API integration.
• Designing and consuming RESTful APIs; building scalable backend services.
• Cloud experience (AWS, GCP, or Azure) and Docker; version control with Git.
• Good communication across engineering, data, and product teams.

Skills

Python

AI/ML systems

LLM-powered systems

AIDLC

Prompt engineering

RAG

RESTful APIs

Cloud platforms

Docker

Git

CI/CD

Kubernetes

Tools

AWS

GCP

Azure

Pinecone

Weaviate

pgvector

FAISS

LangChain

LangGraph

LlamaIndex

Job description

• 10+ years of professional software development experience, with strong, current Python expertise.
• Demonstrable experience delivering at least one AI/ML or LLM-powered system to production and supporting it through its life cycle.
• Practical familiarity with the AI Development Life Cycle (AIDLC): data handling, experimentation, evaluation, deployment, and monitoring.
• Hands-on experience with LLM application development — prompt engineering, RAG, and integrating APIs such as those from major model providers.
• Proficiency designing and consuming RESTful APIs and building scalable backend services.
• Working knowledge with cloud platforms (AWS, GCP, or Azure) and containerization (Docker).
• Solid grounding with version control (Git) and CI/CD workflows.
• Strong communication skills and the ability to work across engineering, data, and product teams.

Preferred Qualifications

• Experience with agentic frameworks and orchestration (e.g., LangChain, LangGraph, LlamaIndex, or multi-agent frameworks).
• Familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector, FAISS) and embedding-based retrieval.
• Exposure to MLOps/LLMOps tooling — MLflow, Weights & Biases, model registries, and feature stores.
• Experience with Kubernetes and infrastructure-as-code.
• Understanding of model evaluation, responsible AI, safety guardrails, and observability for LLM systems.
• Background with data pipelines and streaming (e.g., Kafka, Spark, or Airflow).

Core Tech Stack