We are looking for a highly skilled Assistant Manager (Python & AI Solutions) with strong expertise in Python development, Azure AI Foundry, and Microsoft Copilot integration. The ideal candidate should have hands-on experience in Large Language Models (LLMs), scalable backend systems, and API development, along with sound knowledge of DevOps, analytics, and code review practices.

This role involves designing, developing, and deploying intelligent AI-driven applications using Azure and other modern AI frameworks.

Key Responsibilities

Design, develop, and maintain Python-based backend systems using FastAPI framework.
Work on LLM-based application development and integration with Azure AI Foundry and Microsoft Copilot ecosystem.
Build scalable and modular AI solutions aligned with enterprise-grade performance and security standards.
Collaborate with data scientists, DevOps engineers, and solution architects to deliver robust AI solutions.
Conduct code reviews, enforce coding best practices, and ensure high code quality.
Integrate AI capabilities into business applications using Azure OpenAI Service, Prompt Engineering, and contextual memory design.
Support CI/CD implementation, version control, and deployment automation using DevOps tools.
Work closely with analytics teams to generate insights, optimize performance, and track model accuracy.
Ensure documentation, performance tuning, and maintenance of deployed solutions.

Required Skills & Experience

Strong programming skills in Python and experience with frameworks like FastAPI, Flask, or Django.
Hands-on experience with Azure AI Foundry, Microsoft Copilot, and Azure OpenAI Service.
Good understanding of LLMs, vector databases, embeddings, and prompt engineering concepts.
Experience in building RESTful APIs and integrating third-party APIs.
Familiarity with DevOps practices, CI/CD pipelines, Docker, and Git/GitHub workflows.
Strong understanding of cloud-native architectures and microservices.
Proven experience in code review, unit testing, and maintaining coding standards.
Good analytical and problem-solving skills, with the ability to interpret complex business requirements.
Experience with data analytics, pandas, NumPy, or similar libraries is a plus.

Preferred Qualifications

Exposure to AI/ML model deployment in production environments.
Knowledge of prompt chaining, agent orchestration, or MCP (Model Context Protocol).
Experience with monitoring tools (like Azure Monitor, Grafana, etc.) for performance and reliability.
Strong communication and collaboration skills.

Key CTQ:

Python Engineering Depth Strong hands-on experience with Python and FastAPI; ability to write production-grade, scalable code.
LLM & GenAI Application Experience Practical exposure to LLM-based applications, prompt engineering, embeddings, vector databases, and contextual memory.
Azure AI & Microsoft Copilot Integration Hands-on experience with Azure AI Foundry, Azure OpenAI Service, and Copilot ecosystem integrations.
Backend & API Architecture Experience designing scalable REST APIs and microservices-based architectures.
Cloud & DevOps Readiness CI/CD pipelines, Docker, Git/GitHub workflows, and cloud-native deployment understanding.
Code Review & Engineering Practices Experience in code reviews, enforcing standards, unit testing, and documentation.
Analytics & Data Handling Working knowledge of pandas/NumPy and ability to interpret analytical outputs.
Production Readiness & Monitoring Exposure to deploying AI solutions in production and monitoring performance and reliability.
Problem-Solving & Requirement Interpretation Ability to translate complex business requirements into technical solutions.
Communication & Collaboration Strong cross-team communication, especially with architects, data scientists, and DevOps teams.

Qualification

B.Tech / M.Tech / MCA in Computer Science, Information Technology, or related field.
Certifications in Azure AI / Cloud / Python / Data Science will be an added advantage.

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