Software Engineering Lead – AI Augmented
We are seeking experienced AI Software Engineers to join a forward-looking engineering team focused on AI-augmented SDLC. In this role, you will utilize Generative AI tools across the entire software development lifecycle—from design and coding to testing and documentation—while maintaining high standards of quality, security, and maintainability. This position is ideal for engineers who are adaptable, detail-oriented, and passionate about working at the intersection of modern software engineering and AI.
Key Responsibilities
- Implement AI-Augmented (Agentic) SDLC (Code Generation) for full-stack development
- Design, build, test, and maintain full-stack applications using AI assisted SDLC / Agentic SDLC
- Generate clean, scalable, and maintainable code following best practices using AI assisted tools and AI agents
- Utilize GenAI tools (e.g., GitHub Copilot, Cursor, Claude) to accelerate code generation, testing debugging, and documentation
- Define clear prompts, task specifications, and acceptance criteria to effectively train AI Agents for code generation
- Apply spec-driven development practices to structure and streamline implementation
- Design and develop AI agents, including workflows, tool integrations, and orchestration logic
- Review and validate AI-generated outputs for correctness, security, and performance
- Apply sound engineering judgment to accept, refine, or reject AI-generated solutions
- Refactor and modernize existing applications using AI-assisted approaches to improve maintainability and performance
- Contribute to prompt engineering standards and AI development best practices
Required Qualifications
- 8+ years of experience in software engineering with proficiency in AI and Agentic SDLC implementation
- Strong experience with AI augmented (Agenitc) SDLC and practices
- Strong hands-on experience designing and building enterprise AI agents, multi-agent workflows, and GenAI-powered applications.
- Strong expertise with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar technologies.
- Strong experience implementing RAG, vector databases, tool calling, MCP integrations, memory, context management, and multi-agent orchestration.
- Strong understanding of prompt engineering, context engineering, structured outputs, evaluation frameworks, guardrails, and hallucination reduction.
- Ability to review and validate AI-generated code for quality, security, and performance
- Hands-on experience with GenAI development tools (e.g., GitHub Copilot, Cursor, or similar)
- Understanding of agentic workflows, AI-assisted development, and spec-driven code development
- Experience with prompt engineering and structured AI interactions
- Expereince with Java
Preferred Qualifications
- Experience modernizing legacy enterprise applications using AI-assisted and agentic approaches.
- Bachelor’s degree in Computer Science or related field (or equivalent experience)