INNOVIT USA INC
We are seeking an AI Engineer to drive innovation in our SDLC processes using artificial intelligence and automation. This role is ideal for an engineer passionate about automation and applying AI/ML techniques to improve reliability, observability, and operational workflows. The focus of this role is not to support external AI/ML product teams, but to internally develop AI-driven solutions that optimize SDLC processes, reduce toil, and increase automation maturity across the organization.
Key Responsibilities
Design and implement AI/ML models that improve SDLC processes in domains, such as:
Developer experience and productivity
Intelligent test management using data analytics and predictive techniques
Predictive infrastructure failure detection
Agentic AI, MCP implementation, and RAG techniques
Intelligent alerting and noise reduction
Automated incident classification and root-cause analysis
CI/CD optimization based on historical trends
Using GenAI for IaC
Any other innovative use-cases.
Work closely with Development, DevOps, and Infrastructure teams to identify automation opportunities and pain points.
Develop automation scripts and tooling to reduce manual tasks, operational efficiencies, and user experience.
Build, deploy, and maintain pipelines to train and continuously improve AI models for DevOps use-cases.
Collaborate with Infrastructure, Cloud, and DevOps teams to create architecture/design documents for proposed solutions.
Ensure operational reliability, scalability, and performance of AI-driven automation tooling.
Integrate AI solutions into monitoring.
Experience with Agile Scrum and DevOps methodologies.
Experience working in Developer IDEs, such as Eclipse, IBM Rational Application Developer, STS, etc.
Create technical and design documentation, as required.
Perform system analysis, troubleshooting, diagnosis and problem resolution. Analyze software for defects and performance tuning opportunities.
GitHub Administration
Manage repositories, branching strategies, and access control.
Automate workflows using GitHub Actions or similar CI/CD tools.
Maintain code quality and integration processes.
Define and implement governance rules.
Other duties as assigned.
Required Skills & Qualifications Bachelor s degree in Computer Science, Engineering, or equivalent experience.
3 years in Development/Automation roles.
Strong background in cloud-native infrastructure (AWS, Azure, or Google Cloud Platform).
Proficiency in automation and scripting (Python is preferred, Bash, etc.).
Solid understanding of CI/CD pipelines.
Experience with cloud-native technologies.
Experience applying AI/ML techniques to solve engineering problems (e.g., anomaly detection, classification, clustering).
Familiarity with Python machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
Good understanding of monitoring, logging, and observability tooling.
Preferred Skills Experience with anomaly detection, predictive analytics, or time-series forecasting.
Knowledge of MLOps practices (for internal AI models).
Experience integrating AI solutions into DevOps toolchains and platforms.
Familiarity with infrastructure as code (Terraform, Pulumi, CloudFormation).
Some working experience with Hyper-V Virtual Machine Management.
Asset and service account management.
BMC Helix ticketing system.
CANDIDATE SKILLS AND QUALIFICATIONS 8-Required-Proven ability to administer GitHub Enterprise Cloud
8-Required-Proven ability to analyze and resolve complex issues
8-Required-Supporting and training end users on all levels.
8-RequiredHands-on experience with Continuous Integration Delivery models
3-Preferred-Hands-on experience with large development projects using Agile methodology
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Key Responsibilities
Design and implement AI/ML models that improve SDLC processes in domains, such as:
Developer experience and productivity
Intelligent test management using data analytics and predictive techniques
Predictive infrastructure failure detection
Agentic AI, MCP implementation, and RAG techniques
Intelligent alerting and noise reduction
Automated incident classification and root-cause analysis
CI/CD optimization based on historical trends
Using GenAI for IaC
Any other innovative use-cases.
Work closely with Development, DevOps, and Infrastructure teams to identify automation opportunities and pain points.
Develop automation scripts and tooling to reduce manual tasks, operational efficiencies, and user experience.
Build, deploy, and maintain pipelines to train and continuously improve AI models for DevOps use-cases.
Collaborate with Infrastructure, Cloud, and DevOps teams to create architecture/design documents for proposed solutions.
Ensure operational reliability, scalability, and performance of AI-driven automation tooling.
Integrate AI solutions into monitoring.
Experience with Agile Scrum and DevOps methodologies.
Experience working in Developer IDEs, such as Eclipse, IBM Rational Application Developer, STS, etc.
Create technical and design documentation, as required.
Perform system analysis, troubleshooting, diagnosis and problem resolution. Analyze software for defects and performance tuning opportunities.
GitHub Administration
Manage repositories, branching strategies, and access control.
Automate workflows using GitHub Actions or similar CI/CD tools.
Maintain code quality and integration processes.
Define and implement governance rules.
Other duties as assigned.
Required Skills & Qualifications Bachelor s degree in Computer Science, Engineering, or equivalent experience.
3 years in Development/Automation roles.
Strong background in cloud-native infrastructure (AWS, Azure, or Google Cloud Platform).
Proficiency in automation and scripting (Python is preferred, Bash, etc.).
Solid understanding of CI/CD pipelines.
Experience with cloud-native technologies.
Experience applying AI/ML techniques to solve engineering problems (e.g., anomaly detection, classification, clustering).
Familiarity with Python machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
Good understanding of monitoring, logging, and observability tooling.
Preferred Skills Experience with anomaly detection, predictive analytics, or time-series forecasting.
Knowledge of MLOps practices (for internal AI models).
Experience integrating AI solutions into DevOps toolchains and platforms.
Familiarity with infrastructure as code (Terraform, Pulumi, CloudFormation).
Some working experience with Hyper-V Virtual Machine Management.
Asset and service account management.
BMC Helix ticketing system.
CANDIDATE SKILLS AND QUALIFICATIONS 8-Required-Proven ability to administer GitHub Enterprise Cloud
8-Required-Proven ability to analyze and resolve complex issues
8-Required-Supporting and training end users on all levels.
8-RequiredHands-on experience with Continuous Integration Delivery models
3-Preferred-Hands-on experience with large development projects using Agile methodology
#J-18808-Ljbffr