Ai Engineer

The AI Engineer is a position that evolves and manages the efficient delivery of the company's SaaS portfolio and internal processes.

In this role, you will be responsible for outlining potential areas where AI can be leveraged to optimize processes and enhance capabilities across the portfolio, including identity management, platform integration, and process re-engineering.

Key Responsibilities:

Process Optimization Across Platforms

· Hands-on experience with ETL/ELT design, real-time and batch processing.

· Familiarity with cloud native AI tools such as AWS (Bedrock, Sage Maker), Azure (OpenAI, AI Studio), Microsoft Co-Pilot or Atlassian Rovo.

· Previous experience using AI to summarize and analyze technical or operational content, helping teams quickly understand key points and potential bottlenecks.

· Previous hands-on knowledge of natural language processing to categorize, route, and prioritize tasks or requests, improving response time and efficiency across teams.

· Previous role in collecting, analyzing, and preprocessing large datasets to develop and train AI models.

· Collaborate with data engineers to design and implement data pipelines and architectures.

Operational Intelligence

· Apply AI to uncover trends and actionable insights from engineering and operational data, reducing reliance on manual analysis.

· Use AI to review processes performance and collaboration data, helping identify opportunities for process improvement and efficiency.

· Design and integrate AI solutions into products and workflows through APIs and other integration methods.

· Work with modern deployment and orchestration practices to ensure scalability and reliability of AI-enabled solutions.

· Familiarity with automation platforms and frameworks, leveraging the right tools for process automation.

· Ability to distinguish where to apply traditional automation versus AI-driven approaches, ensuring fit-for-purpose solutions.

Qualifications:

· Proven experience in AI/ML engineering, preferably in a software development or Dev Ops context.

· Strong proficiency in Python and experience with ML frameworks (e.g., PyTorch, Tensor Flow).

· Familiarity with LLMs, prompt engineering, and APIs like OpenAI, Hugging Face, etc.

· Experience working with development tools such as Git Hub, Jira, and CI/CD pipelines.

· Understanding of software engineering workflows and pain points.

· Excellent problem-solving and communication skills.

Experience:

· At least 3-5 years of experience in AI and machine learning development.

· Experience working with large datasets and developing scalable AI systems.