AI Program Analyst

Role overview

We are seeking an analytically driven AI Program Analyst to work at the intersection of AI, engineering workflows, and business outcomes.

This role focuses on identifying high-impact AI opportunities across the organization, translating technical initiatives into measurable business value, and supporting leadership in evaluating and scaling AI-driven improvements. The ideal candidate is comfortable engaging with engineering teams, analyzing workflows, and building a structured understanding of how AI can drive productivity, efficiency, and operational excellence.

This position offers strong exposure to real-world AI implementation and provides a foundation for growth into AI strategy, architecture, or enterprise transformation roles.

Key responsibilities:

1. AI opportunity analysis and use case development (≈70%)

• Analyze how AI can improve engineering productivity, operational efficiency and internal workflows.
• Collaborate with delivery teams, architects, and practice leads to understand ongoing AI initiatives and experiments.
• Identify opportunities for AI-driven automation to reduce manual effort and improve delivery outcomes.
• Develop structured AI use cases including:
  • Problem definition and scope
  • Technical approach
  • Productivity, efficiency and ROI impact

2. Feasibility and risk assessment

• Evaluate AI opportunities across engineering, delivery, HR, finance and operations.
• Maintain a centralized repository of validated AI use cases and automation initiatives.
• Quantify operational impact using productivity, cost and efficiency metrics.

3. AI prototyping and internal automation (≈25%)

• Build lightweight prototypes to validate AI use cases and automation opportunities.
• Develop basic AI assistants using tools such as Microsoft Copilot or similar platforms.
• Prototype document processing workflows (classification, summarization, metadata extraction).
• Automate repetitive internal tasks such as reporting, document processing and data summarization.
• Support AI Architects in evaluating new tools, frameworks and models.
• Conduct rapid experiments to assess feasibility and limitations of AI solutions.

4. Program intelligence and strategic support (≈5%)

• Support the Program Director in tracking cross-functional initiatives.
• Maintain visibility into program progress, dependencies and risks.
• Synthesize discussions into actionable insights and clear next steps.
• Track execution and identify blockers across teams.
• Prepare structured summaries and updates for leadership.

Required skills and qualifications:

• Bachelor’s degree in Computer Science, Engineering, IT, or related field.

• 0–2 years of experience (internships/projects in AI, analytics, or engineering are acceptable).

  Strong capabilities in:

• Analytical thinking and structured problem-solving.

• Understanding technical concepts and engineering workflows.

• Translating technical ideas into business impact.

• Familiarity with AI tools such as ChatGPT, Claude, Microsoft Copilot, or similar platforms.

• Strong skills in Excel and PowerPoint for analysis and reporting.

• Clear written and verbal communication skills.

Nice to have skills:

• Exposure to Python or basic scripting for automation.
• Understanding of AI/ML concepts or data analysis.
• Experience working with dashboards or data visualization tools.
• Familiarity with business metrics, ROI calculations, or process optimization.

Must have skills:

• Strong analytical and problem-solving skills.
• Understanding of technical concepts and engineering workflows.
• Familiarity with AI tools such as ChatGPT, Claude, or Microsoft Copilot.
• Proficiency in Excel and PowerPoint.

Desired attributes:

• Highly curious and proactive in exploring new AI tools and technologies.
• Strong interest in understanding systems, workflows, and processes.
• Structured thinker with a rigorous, analytical approach.
• Enjoys experimentation and rapid prototyping.
• Ability to connect engineering work to measurable business outcomes.
• Strong listening and interviewing skills to extract insights from teams.
• Ability to translate complex technical concepts into clear, compelling narratives.

Interview process

2 rounds of discussion.