Job Summary

To be responsible for managing technology in complex projects ,providing technical guidance and ensuring successful delivery of solutions.

Key Responsibilities

1. To be responsible for providing technical guidance to a team of developers, enhancing their technical capabilities and increasing productivity.
2. To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects.
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.

Skill Requirements

"AI Agent Development & LLM Integration
• Build AI agents using frameworks like LangGraph, Autogen, Crew, or PydanticAI.
• Design and optimize prompt engineering workflows for LLMs (e.g., GPT, Claude, LLaMA).
• Develop modular, reusable components for agent orchestration and task automation.
Model Deployment & Infrastructure
• Deploy models using Databricks and Azure ML, integrating with enterprise-grade systems.
• Implement APIs, WebSockets, and event-driven architectures for real-time AI services.
• Collaborate with platform teams to ensure scalable and secure deployments.
Development & Automation
• Work with CI/CD pipelines using Jenkins to automate testing and deployment.
• Use GitHub Copilot, Windsurf, Codeium, or similar tools to accelerate development.
• Maintain high code quality and documentation standards using Git, Jira, and Confluence
Must-Have Skills:
• 3–5 years of experience working Machine Learning / Artificial Intelligent or related fields.
• 1+ years of experience building Generative AI Applications for enterprise, deep understanding of workflows like RAG.
• Strong proficiency in Python and modern development practices.
• Hands-on experience with LLMs and prompt engineering.
• Experience building AI agents using at least one of Lang Graph, Crew, or PydanticAI.
• Familiarity with Databricks and cloud-native deployment strategies.
• Understanding of REST APIs, WebSockets, and event-driven systems.
• Familiarity with SDLC best practices and agile methodologies.
• Proficiency with using CI/CD tools (Jenkins) and version control (Git).
• Comfortable using AI-augmented development tools for rapid prototyping.
Nice-to-Have Skills:
• Exposure to MLOps/LLMOps workflows and model monitoring.
• Knowledge of enterprise security, compliance, and governance in AI systems.
• Exposure to best practices for code and model lifecycle management.
Soft Skills & Mindset:
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Self-starter with a growth mindset and curiosity for emerging AI trends.
• Ability to work in cross-functional teams and adapt to evolving priorities."

Other Requirements

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