at Gamma Technologies in Westmont, Illinois, United States
Job Description
- Perform DevOps 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.
- DevOps 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 CloudFormation Templates / Terraform / Kubernetes yaml files / Ansible. (Preferred tool: CloudFormation Templates, Ansible)
- Database: Can manage structured/unstructured data on platforms such as DynamoDB, PostgreSQL, or similar
- Version Control Systems: Experience with Git or Perforce code repositories. (Preferred tool: GitLab)
- 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, LangChain, or Model Context Protocol (MCP) for agent orchestration and retrieval optimization
- Cost Optimization: Knowledge of cost optimization strategies for large-scale AI workloads (spot instances, batching, inference caching)
- Security: Experience securing AI pipelines and models against adversarial inputs or data leakage
What We Can Offer You
- Competitive total rewards program with health and financial benefits (401K and profit sharing).
- Flexible work options. This role will require you to be in the office 60% of the time.
- Generous vacation, sick days, holidays and including parental leave.
- Onsite fitness center.
- Growth and development opportunities.
- The expected annual base salary range for this role is $110,000 - $120,000. Please note the salary information shown above is a general guideline only. Salaries are based upon candidate skills, experience, qualifications, as well as market and business considerations.
