AIML Engineer

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 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:

Bachelors degree in Computer Science Engineering or equivalent experience.

3 years in Development/Automation roles.

Strong background in cloud-native infrastructure (AWS Azure or GCP).

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