System Analyst

System Analyst

Highlights

• Design and implement multiple sub-systems for an in-house developed AI-integrated platform across various business domains.
• Oversee the development of secure, scalable, and AI-enhanced solutions using Python, NodeJS and React.
• Leverage prompt engineering and vibe coding for innovative development practices.
• Manage cross-functional teams and offshore team to deliver cutting-edge, AI-driven solutions while aligning with business goals and compliance standards.
• Implement secure SDLC practices with AI, including threat modelling, secure coding, and vulnerability management, to ensure system integrity.
• Take a hands-on approach to project delivery, providing technical guidance and contributing to solutions to meet project goals, including hands-on coding and review.

Role and Responsibilities

• Lead and work with offshore development team (2-3 per team) in developing and deploying AI-enhanced software solutions, ensuring high performance, reliability, and security on business-oriented solution and system design.
• Collaborate with stakeholders to define AI strategies and implement prompt engineering best practices for optimizing AI model outputs.
• Foster a culture of innovation through vibe coding and other AI-assisted development methodologies.
• Mentor and guide teams in adopting new AI technologies and secure development practices, ensuring alignment with organizational objectives.
• Drive the adoption of Agile methodologies for AI-focused projects, ensuring iterative delivery and continuous improvement.
• Ensure security is integrated throughout the SDLC, from requirements gathering to deployment and maintenance.
• Handle and understand all functional test arrangements: such as vulnerability test, load test, stress test, performance test with k6 or similar approach
• Take an active, hands-on role in project delivery, balancing strategic oversight with technical contributions to overcome challenges and meet deadlines.

Key Competencies & Experience Requirements

• 4+ years of hands-on experience in system design and architecture, with a focus on AI integration and agentic solutions.
• Proficiency in Python, NodeJS and React, with experience in building AI-driven applications, knowledge of Java Spring Boot, and Spring Cloud will also be considered
• Expertise in prompt engineering to optimize AI model performance and ensure accurate, contextually relevant outputs.
• Familiarity with AI tools and frameworks, such as Model Context Protocol (MCP), Agentic Frameworks, AI Safety Framework, to ensure responsible AI deployment would be an advantage.
• Experience with vibe coding practices in both frontend and backend knowledge, utilizing AI assistants (e.g., RooCode, Cline, Cursor, WindSurf, GitHub Copilot) for rapid prototyping and development on full SDLC.
• Strong understanding of cloud platforms (AWS, Azure, GCP) for scalable solution deployment.
• Deep knowledge and hands-on SDLC processes, with a particular emphasis on integrating security throughout the lifecycle (DevSecOps).
• Ability to lead projects with a hands-on approach, balancing managerial responsibilities with technical contributions to ensure successful delivery.
• Knowledge of security standards and best practices, such as OWASP, ISO 27001, or ISO 42001, and experience applying them in software development.
• Team leadership skills to manage and mentor diverse team members in adopting new AI technologies and secure practices.
• Strong communication skills to articulate technical concepts, AI strategies, and security requirements to both technical and non-technical stakeholders.

Skills

• Passionate about leveraging AI to optimize operations and drive innovation across inhouse development platforms.
• Proficient in Agile methodologies, with experience leading AI-focused projects iteratively.
• Strong communication skills to convey AI strategies, technical designs, and business value effectively.
• Committed to staying updated on AI advancements, including Model Context Protocol, Agentic Frameworks, safety frameworks, prompt engineering, and AI-assisted coding trends.
• Able to perform hands-on technical work when needed, demonstrating a deep understanding of the technologies used.