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AI Backend Developer

Summary

Build and deploy backend services for AI/ML models, integrating LLMs, vector databases, and RAG pipelines using Python, FastAPI, and cloud platforms.

Talent Acquisition Leader | Hiring Cloud Professionals Globally

About us:

Intuitive is an innovation-led engineering company delivering business outcomes for 100’s of Enterprises globally. With the reputation of being a Tiger Team and a Trusted Partner of enterprise technology leaders, we help solve the most complex Digital Transformation challenges across following Intuitive Superpowers:

  • Modernization & Migration
    • Application & Database Modernization
    • Cloud Native Engineering, Migration to Cloud, VMware Exit
    • FinOps
  • Data & AI/ML
  • Cybersecurity
    • Infrastructure Security
    • Application Security
    • Data Security
  • SDx & Digital Workspace (M365, G-suite)
    • SDDC, SD-WAN, SDN, NetSec, Wireless/Mobility
    • Email, Collaboration, Directory Services, Shared Files Services
  • Intuitive Services:
    • Professional and Advisory Services
    • Elastic Engineering Services
    • Managed Services
    • Talent Acquisition & Platform Resell Services

About the job:

Start Date: Immediately

# of Positions: 1

Position Type: Full Time

Location: Remote across Canada/ USA

Key Responsibilities

  • Design and develop backend services and APIs to support AI/ML models in production.
  • Integrate LLMs, vector databases, and RAG pipelines into backend systems.
  • Build scalable, secure, and high-performance microservices for AI applications.
  • Implement data pipelines for training, fine-tuning, and serving AI/ML models.
  • Collaborate with frontend, ML, and LLMOps teams to deliver end-to-end AI features.
  • Monitor, optimize, and troubleshoot performance, scalability, and latency issues.
  • Ensure compliance with security, governance, and regulatory standards.

Required Skills & Qualifications

  • Strong backend development experience with Python
  • Proficiency in RESTful APIs, FastAPI, Flask
  • Experience with cloud platforms (AWS, Azure, GCP) for AI/ML deployments
  • Familiarity with LLMs, vector DBs (Pinecone, Weaviate, Milvus, PGVector), RAG architectures
  • Experience with containerization (Docker, Kubernetes)
  • Strong knowledge of databases (SQL & NoSQL)
  • Good understanding of CI/CD pipelines, observability, and logging tools

Nice to Have

  • Experience with LangChain, LlamaIndex, or other agentic frameworks
  • Knowledge of MLOps / LLMOps practices
  • Exposure to streaming systems (Kafka, Pub/Sub)
  • Prior work with GenAI, chatbots, multimodal AI applications

Seniority level

  • Mid-Senior level

Employment type

  • Contract

Job function

  • Information Technology

Industries

  • IT Services and IT Consulting

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