Technical Lead AI

Weekday 1; Mumbai; On-site; INR 6,000,000 - 9,000,000; Full time

Job summary

Weekday 1 client is looking for a senior leader to head AI/ML operations and platform engineering, ensuring technical excellence in the AI/ML tech landscape and driving adoption across business units.

The role involves mentoring AI Engineering, Data Engineering and Platform teams, guiding architecture, evaluating tools and cloud services (Azure AI, AWS SageMaker, Vertex AI), and enforcing observability, security and governance across AI/ML solutions.

Qualifications

• Experience leading AI/ML platforms and operations across large orgs.
• Strong background in production AI/ML systems and cloud-native architectures.
• Leadership in architecture, mentoring and cross-functional collaboration.
• Proven ability to translate business needs into scalable AI/ML solutions.

Responsibilities

• Provide technical leadership and mentoring to AI Engineering, Data Engineering, and Platform teams.
• Drive enablement of AI/ML platforms, tooling, and best practices across the organization.
• Oversee architecture guidance for AI/ML solutions and cloud service integration.
• Evaluate and integrate AI/ML tools and services (Azure AI, AWS SageMaker, Vertex AI).
• Establish monitoring, logging, and observability standards for AI/ML systems.
• Ensure compliance, security, and governance across AI/ML solutions.
• Partner with solution architects to translate requirements into scalable AI/ML platforms.

Skills

ML Frameworks

AI/ML Platforms

LLMs & GenAI

Data Processing

Cloud Platforms

Container Orchestration

MLOps & Deployment

ETL Tools

Monitoring & Observability

Scripting & SQL

Git & Version Control

Tools

Databricks

Kubeflow

MLflow

DVC

Weights & Biases

Job description

This role is for one of Weekday’s clients

Min Experience: 12+ years
Location: Mumbai, Maharashtra, India
JobType: full-time

The incumbent shall be responsible for leading AI/ML operational and platform engineering functions across the organization. The focus of this role is to provide and ensure technical excellence in the AI/ML technology landscape and drive the adoption of AI solutions across business units.

Requirements

Relevant Experience:

• 10 years’ experience in IT, software engineering, or data science related positions
• 5 years of direct experience with AI/ML technologies, platforms, and solutions in production environments.
• 3 years in technical leadership, architecture, or senior engineering role.
• Experience in Designing and implementing large-scale AI/ML solutions and systems.
• Experience working with cloud platforms and understanding of cloud-native architectures.
• Experience with DevOps, CI/CD pipelines, and containerized deployments.

Responsibilities:

• Deep dive technical investigation, analysis and troubleshooting across AI/ML technology stacks, frameworks, and infrastructure using appropriate diagnostic and monitoring tools.
• Provide technical leadership and mentoring to AI Engineering, Data Engineering, and Platform teams, fostering a culture of technical excellence and continuous improvement.
• Drive the enablement of AI/ML platforms, tooling, and best practices across the organization.
• Provide architecture guidance and technical oversight for AI/ML solution design, implementation, and optimization.
• Lead the evaluation, selection, and integration of AI/ML tools, frameworks, and cloud services (e.g., Azure AI, AWS SageMaker, Google Vertex AI).
• Establish and maintain monitoring, logging, and observability standards for AI/ML systems and models.
• Investigate opportunities for optimization of AI/ML technology stacks, including model performance tuning and infrastructure efficiency.
• Work with solution architects and business stakeholders to translate business requirements into technical AI/ML solutions.
• Provide support and enablement for containerized and cloud-native environments, specifically Kubernetes and serverless platforms.
• Ensure compliance, security, and governance best practices are implemented across all AI/ML solutions.
• Stay current with emerging AI/ML technologies, frameworks, and industry best practices.

Mandatory Skills:

• Machine Learning Frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost)
• AI/ML Platforms (Azure AI, AWS SageMaker, Google Vertex AI, Databricks)
• Large Language Models and GenAI (transformers, RAG, prompt engineering, LLMOps)
• Data Processing and Analytics (Spark, Hadoop, pandas, SQL)
• Cloud Platforms (Azure, AWS, GCP)
• Container Orchestration (Kubernetes, Docker)
• MLOps and Model Deployment tools (MLflow, Kubeflow, DVC, Weights & Biases)
• Data Engineering and ETL tools
• Monitoring, Logging, and Observability tools (Prometheus, ELK, Grafana, DataDog)
• Scripting and Programming Languages (Python, Java, Scala, SQL)
• Git and Version Control Systems

Must-have skills

AI/ML technology, AI/ML operational

Good-to-have skills

Engineering Manager