DevOps and GenAI Backend Developer

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This range is provided by Gamma Technologies. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

Who We Are

GT, a leading multi-physics CAE simulation software provider, develops a suite of integrated solutions that guides and accelerates the engineering transformation of today’s products in the transportation, power generation, and industrial equipment industries.

At Gamma Technologies, our people are the driving force behind our success. We are looking for a Dev Ops and GenAI Backend Developer who shares our passion for authentic innovation, trusted partnerships, bold decisions and a relentless focus on customer success.

What You Will Do

You’ll be at the forefront of blending cloud infrastructure and AI innovation by designing, implementing, and maintaining the backbone that allows our Generative AI services to operate reliably and scale effortlessly. You will also contribute Dev Ops expertise in areas outside of GenAI, such as our next generation modeling environment GT-Play and on-demand cloud computing services.

• Perform Dev Ops activities including cloud architecture definition, deployments, CI/CD pipelines enhancement, maintenance and system monitoring for Generative AI applications, and other cloud-based software.
• Create, maintain, and update architecture as code and pipeline scripts used to deploy products and their cloud architecture.
• Operate a wide range of cloud services deployed on Amazon Web Services (i.e. Amazon Bedrock, Amazon Cognito, EC2, ECS, SES, ELB)
• Work on hardening security of cloud-based environment (architecture and software) to match compliance with strong information security standards (like TISAX or ISO 27001)
• Troubleshoot incidents and coordinate with developers of products involved to provide support and fixes.

What You Will Bring

• BS/MS in Computer Science, Engineering, AI, or related field / equivalent professional experience.
• AWS Cloud Architecture: Strong hands-on experience in managing and deploying web applications and cloud architecture on AWS. Ability to create Cloud Architecture for a given web-based product from scratch with focus on auto-scaling, load balancing, data migration and cost optimization.
• AI Applications: Proven track record of deploying and maintaining Machine Learning (ML) / Large Language Model (LLM) applications in production environment with active users.
• Dev Ops background: Minimum of 3 years’ experience and proficiency in Python for automating pipelines, integrating AI workflows, and optimizing deployments.
• Secure Infrastructure Practices: Comfortable operating within environments that enforce strict access controls and compliance-driven workflows. Contribute to ensure systems remain resilient and protected.
• Collaboration: Experience working closely with developers to manage staging environments, troubleshoot and debug with them to understand the inner workings of various products.

Technical Skills and Tools:

• AI Awareness: Basic understanding of Generative AI concepts (RAG, agents, data processing, prompt engineering); ability to work with engineers on prompt and pipeline improvements. Knowledge of GPU infrastructure management, token usage optimization, and scaling strategies for API-based LLMs
• Automated Deployment Tools: Proficiency with tools dedicated to automated deployment like Cloud Formation Templates / Terraform / Kubernetes yaml files / Ansible. (Preferred tool: Cloud Formation Templates, Ansible)
• Database: Can manage structured/unstructured data on platforms such as Dynamo
  
  DB, Postgre
  
  SQL, or similar
• Version Control Systems: Experience with Git or Perforce code repositories. (Preferred tool: Git Lab)
• Coding/Knowledge of the stack: good knowledge of Java, Python and web frontend frameworks (Angular), and understand how to read and analyze stack trace for these

Relevant additional AI experience:

• Agents: Basic Familiarity with frameworks like CrewAI, Lang Chain, or Model Context Protocol (MCP) for agent orchestration and retrieval…