Senior AI FDE - Azure AI Foundry

Koantek

India

Remote

INR 4,000,000 - 7,000,000

Full time

14 days+

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Job summary

Koantek is seeking a Senior AI FDE to lead client-facing AI/ML implementations. You will design, deploy, and maintain production-grade Generative/Agentic AI and traditional ML solutions with a focus on MLOps/AIOps, scalable architectures, and robust data pipelines.

The role emphasizes hands-on development, multi-agent orchestration, RAG systems, and seamless integration with the Microsoft stack within a remote, international client environment.

Qualifications

  • Agentic AI & Azure AI Foundry experience in production settings is required.
  • Strong Python development skills for data-intensive AI/ML workloads.
  • Hands-on MLOps lifecycle management, model versioning, monitoring and deployment.
  • Experience delivering client-facing AI/ML solutions with effective communication.

Responsibilities

  • Lead and execute end-to-end AI/ML projects for clients.
  • Design and maintain production-grade AI/ML pipelines with CI/CD.
  • Architect end-to-end AI/ML systems combining traditional ML and Generative AI.
  • Manage infrastructure for production deployment including Docker and orchestration.
  • Collaborate on distributed computing with Spark and related tech.
  • Document client engagements and knowledge transfer activities.

Skills

Agentic AI
Azure AI Foundry
Python
MLOps
Docker
Spark
RAG architectures
Communication

Tools

Databricks

Job description

Senior AI FDE - Azure AI Foundry /Data Scientist / MLOps Consultant

We are seeking an experienced and highly technical Senior AI FDE to join our customer-facing consulting team. This remote role requires a blend of advanced Generative AI and Machine Learning (ML) expertise, deep knowledge of production MLOps/AIOps principles, and a proven track record in client-facing implementation. A successful candidate will be instrumental in designing, deploying, and maintaining production-grade Generative and Agentic AI solutions and traditional machine learning models for our diverse client base.

Key Responsibilities
  • Technical Leadership & Client Engagement: Serve as a primary technical consultant, leading and executing end-to-end AI/ML project implementations directly with clients, translating complex business problems into robust technical solutions. Exhibit excellent communication, presentation, and stakeholder management skills to clearly articulate technical findings, proposals, and project status to both technical and non-technical audiences.
  • MLOps & AIOps Pipelines: Design, build, and maintain production-grade AI and ML pipelines, focusing on continuous integration, continuous delivery (CI/CD), and advanced MLOps/AIOps practices to ensure reliability and scalability of models.
  • Generative & Agentic AI Implementation: Implement and optimize cutting-edge Generative and Agentic AI applications, demonstrating hands-on experience with technologies like multi-agent orchestration, agent evaluation, and Retrieval Augmented Generation (RAG) Systems in a production setting.
  • System Architecture: Architect end-to-end AI/ML systems, designing both traditional Machine Learning- and Generative AI-based solutions based on customer requirements.
  • Infrastructure Management: Manage underlying solution infrastructure necessary for production deployment, demonstrating proficiency in technologies such as Docker, pipeline orchestrators, and cloud ecosystem integration.
  • Data & Distributed Computing: Leverage expertise in distributed computing frameworks, specifically in scalable machine learning and high-performance data processing (e.g., using technologies like Apache Spark).
  • Practice Growth & Documentation: Contribute to the strategic growth of the AI FDE Practice, including participation in technical assignments and knowledge transfer activities. Ensure all client engagements and training activities are properly documented and reported via designated partner platforms.
Candidate Experience & Required Qualifications

An ideal candidate will have the following experience:

  • Agentic AI & Azure AI Foundry (Must): Practical experience in building AI agents, agentic workflows, and experimenting with Azure AI Foundry to solve real-world problems.
  • General Microsoft Stack (Must): Practical experience navigating and integrating solutions across Microsoft’s cloud, data, and enterprise application ecosystem.
  • Modern Gen AI Foundations (Must): Understanding of multi-agent orchestration, RAG architectures, MCP, text-to-SQL architecture, and action-oriented AI.
  • Professional Experience: 4+ years of hands‑on professional experience developing, deploying, and managing Generative/Agentic AI or Machine Learning systems, with a mandatory requirement for productionizing and maintaining models in a live environment.
  • Consulting & Solutions Architecture: 3+ years of experience in a customer‑facing consulting or solutions architect role, focused on technical implementation and delivery.
  • Communication: Excellent verbal and written communication skills for effective client and internal team interaction.
  • Technical Core:
  • Expertise in Python for data‑intensive and scalable AI/ML applications.
  • Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, and automated deployment best practices.
  • Demonstrable experience with infrastructure management, encompassing containerization (Docker) and data pipeline orchestration.
  • Demonstrated commitment to continuous learning in emerging AI/ML fields.
Preferred Qualifications
  • Databricks (Preferred, but not necessary): Prior hands‑on experience with the Databricks platform, especially for Generative and Agentic AI in production workflows.
  • Large-Scale Data Processing: Knowledge of specific tools and techniques used in large-scale data processing and lakehouse database architectures.
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