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AI Platform Engineer (Gen AI)

Role overview

Qualifications

  • 8+ years of professional experience in software engineering or platform engineering
  • Strong development experience in Python or Java
  • Hands-on experience building production-grade Generative AI systems
  • Experience deploying and operating systems in cloud environments

Responsibilities

  • Design, build, and maintain platform infrastructure for Generative AI applications
  • Develop scalable backend services using Python or Java
  • Implement end-to-end DevOps practices, owning the lifecycle from development through deployment and monitoring
  • Design and manage CI/CD pipelines using tools such as GitHub Actions or Jenkins

Key facts

Hard skills

About the company

Veltris logo

Veltris

  • IT Services & Consulting
  • 501–1,000
Veltris – Innovate, Accelerate, Transform to enable technology-driven Enterprise, Business, and Industry transformations. We are a Digital Product Engineering Services partner that delivers next-generation technology and industry solutions across the healthcare, technology, communications, manufacturing and financial sectors. Veltris enables clients to build, modernize, and monetize smarter products and platforms powered by Connected Industry AI solutions. Through an experience-centric approach, agile delivery, and differentiated talent, Veltris helps businesses optimize product development cycles, monetize platform investments, and drive transformative outcomes in niche micro industries.

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Job description

This is a remote position.

Job Title: AI Platform Engineer (Gen AI)

Experience: 8 Years
Location: US

Job Summary

We are looking for an experienced Platform Engineer specializing in Generative AI to design, build, and operate scalable AI platforms that support advanced AI capabilities such as AI Agents, Retrieval-Augmented Generation (RAG), and Knowledge Graph systems.

The ideal candidate will combine strong software engineering skills with cloud-native platform development and DevOps practices to deliver reliable, production-grade AI solutions.


Key Responsibilities

·        Design, build, and maintain platform infrastructure for Generative AI applications.

·        Develop scalable backend services using Python or Java.

·        Build and operate production-grade AI systems, including:

* AI Agents
* Retrieval-Augmented Generation (RAG)
* Knowledge Graph based systems

·        Implement end-to-end DevOps practices, owning the lifecycle from development through deployment and monitoring.

·        Design and manage CI/CD pipelines using tools such as GitHub Actions or Jenkins.

·        Implement Infrastructure as Code (IaC) using Terraform.

·        Deploy and manage applications on cloud platforms using both:

* Cloud-native services
* Containerized, cloud-agnostic environments

·        Work closely with data scientists, ML engineers, and platform teams to deliver scalable AI infrastructure.


Requirements

Required Skills & Qualifications

·        8+ years of professional experience in software engineering or platform engineering.

·        Experience from internships, prototypes, or personal projects will not be considered toward the required years.Strong understanding of system integration and API design with CRM related toolsets

·        Strong development experience in Python or Java.

·        Hands-on experience building production-grade Generative AI systems

·        Experience with AI Agents & Retrieval-Augmented Generation (RAG)

·        Experience building Knowledge Graph platforms

·        Expertise in Graph databases, Metadata ontology, Graph-based RAG architectures

·        Strong experience in DevOps culture and practices

·        Hands-on experience with:

·  CI/CD pipelines (GitHub Actions or Jenkins)

·  Infrastructure as Code (Terraform)

·       Experience deploying and operating systems in cloud environments: Cloud Native(AWS S3, Lambda, AWS batch, AWS ECS) and Kubernetes-based services.

Preferred / Nice-to-Have Skills

·        Experience building AI platforms or ML platforms at scale

·        Experience with LLM orchestration frameworks (LangChain, LlamaIndex, etc.)

·        Familiarity with vector databases and embedding systems

·        Experience in distributed systems and microservices architecture



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