Principal Software Engineer

About the Role

Principal Software Engineer (GenAI Enablement)

Key Responsibilities

1. GenAI Training & Developer Enablement

• Deliver

  GenAI training programs, workshops, demos, and hands-on labs

  for engineering teams.
• Build best-practice playbooks, reusable training material, and capability uplift frameworks.
• Coach developers in prompt engineering, LLM usage, and AI-assisted coding patterns.

2. Engineering Technical Leadership

• Provide strong hands-on guidance across the

  end-to-end SDLC

  with expertise in:

• Java–Angular

  or

  NodeJS–Angular

• Spring Boot

• Microservices

• AWS Cloud

• Support teams in integrating GenAI for design, coding, testing, debugging, and documentation.
• Conduct architecture reviews, solution design discussions, and quality assessments.

3. GenAI Tools & Accelerator Adoption

• Promote adoption of

  GitHub Copilot, Microsoft Copilot, Azure OpenAI

  , and GenAI-enabled testing accelerators.
• Define best practices, standards, and guardrails for safe and effective tool usage.
• Evaluate emerging GenAI tools and recommend adoption strategies.

4. Hands-On Technical Support

• Assist engineering teams in refining prompts and improving GenAI output quality.
• Guide the integration of AI-driven workflows into existing CI/CD pipelines.
• Act as a GenAI SME for architecture, solution patterns, and feasibility assessments.

5. GenAI POC Identification & Delivery

• Collaborate with engineering leadership to identify, evaluate, and prioritize

  high-impact GenAI PoCs

  .
• Lead PoC development—architecture, design, implementation, testing, and performance evaluation.
• Present PoC outcomes, metrics, and recommendations to stakeholders and leadership teams.

Required Skills & Experience

• 10–14 years of strong hands-on engineering experience.
• Deep technical expertise in:
• ✓

  Java–Angular or NodeJS–Angular

• ✓

  Spring Boot

• ✓

  Microservices-based architectures

• ✓

  AWS Cloud (EC2, Lambda, API Gateway, RDS, S3, CI/CD, etc.)

• Strong understanding of

  GenAI, LLMs, prompt engineering

  , and AI-assisted development workflows.
• Experience conducting developer workshops, training sessions, or tech enablement programs.
• Practical exposure to

  GitHub Copilot, Microsoft Copilot, Azure OpenAI

  , or similar GenAI tools.
• Strong problem-solving, architectural thinking, and debugging skills.
• Excellent communication, leadership, and mentoring skills.