Python AI Engineer

Title                                       :  Python AI Engineer

Location                               : Phoenix ,AZ (Local Only)

Duration                              :12 Months

Rate                                        : $52/Hr On C2C

Relevant Experience (in Yrs.)    :

Detailed Job Description:
ROLE_DESCRIPTION
 Design, develop, maintain and evolve enterprise knowledge-base infrastructure and AI-enabled backend services using Python and FastAPI.
 Build and optimize ingestion, chunking, embedding, vector indexing, semantic retrieval, reranking, context construction and grounded RAG pipelines.
 Develop LangChain/LangGraph-based agent workflows and reusable agent-runtime capabilities including tool calling, state management, retries, validation, guardrails and human approval where required.
Integrate LLMs and enterprise knowledge sources securely through reusable APIs and services.
Implement PostgreSQL/vector database persistence, metadata filtering and  retrieval     patterns optimizedforaccuracy, latency and scale.
Cloud-Native Delivery & Production Engineering
Containerize services with Docker and deploy/manage them on Kubernetes.
Build and maintain CI/CD pipelines using GitHub Actions, Jenkins or equivalent tools, including automated testing and deployment controls.
 Implement logging, tracing, metrics, dashboards and alerts using OpenTelemetry, Prometheus, Grafana and enterprise monitoring tools.
Diagnose and resolve issues across APIs, retrieval pipelines, agent execution, databases, containers and distributed infrastructure.
 Improve performance, reliability, security, scalability and cost efficiency of production AI services.
Quality, Evaluation & Collaboration
Establish automated tests and evaluation approaches for APIs, retrieval quality, grounded responses and agent behavior.
Apply secure coding, access controls, audit logging, prompt/output validation and responsible-AI practices

Must Have Skill

·         Python 3.11 

·         FastAPI

·         LangChain / LangGraph

·         Generative AI / LLM

·         RAG (Retrieval Augmented Generation)

·         AI Agents / Agentic AI

·         Vector Database / pgvector / PostgreSQL

·         Docker / Kubernetes / CI/CD