Tech Lead – AI & Engineering

Master Mind Consultancy; Chennai; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Master Mind Consultancy is seeking a senior technology leader to architect and deliver scalable enterprise AI/ML solutions in Chennai. You will guide architecture, design, and development, driving cloud-enabled initiatives, AI governance, and robust data platforms.

You will mentor teams, collaborate with stakeholders, and ensure production readiness, security, and performance while promoting best practices and continuous improvement.

Qualifications

• Bachelor's or Master's degree in Computer Science, IT, Engineering, Data Science, or a related field.
• Strong background in software engineering, AI/ML engineering, data engineering, or related technology domains.
• Experience in technical leadership, architecture, and engineering team management.
• Solid understanding of software architecture, design patterns, APIs, microservices, and distributed systems.
• Hands-on experience with AI/ML, GenAI, LLMs, RAG, or related AI technologies.
• Strong experience with at least one major cloud platform: AWS, Azure, or GCP.
• Hands-on knowledge of Docker, Kubernetes, CI/CD, and DevOps practices.
• Good understanding of databases, data architecture, and data engineering fundamentals.
• Experience delivering production-grade enterprise applications and working with Agile/Scrum methodologies.
• Strong problem-solving, debugging, architecture, and technical decision-making skills.
• Excellent communication, stakeholder management, mentoring, and team coordination skills.
• Ability to balance hands-on engineering, architecture, team leadership, and stakeholder-facing responsibilities.

Responsibilities

• Lead the architecture, design, and development of scalable enterprise technology solutions.
• Drive the development and deployment of AI/ML and GenAI solutions, including LLMs, RAG, vector databases, AI agents, and model orchestration.
• Provide technical leadership across software engineering, APIs, microservices, distributed systems, and data platforms.
• Design cloud-native solutions using AWS, Azure, or GCP, ensuring scalability, security, and performance.
• Drive CI/CD, DevOps, containerization, and deployment practices using Docker and Kubernetes.
• Oversee data engineering solutions involving data pipelines, ETL/ELT, Spark, Kafka, and cloud data platforms.
• Conduct architecture and code reviews, establish engineering standards, and resolve complex technical issues.
• Lead, mentor, and develop engineering teams while promoting best practices and continuous improvement.
• Collaborate with business stakeholders and cross-functional teams to translate business requirements into technical solutions.
• Ensure production readiness, system reliability, responsible AI practices, and continuous performance monitoring.

Skills

Technical leadership

AI/ML engineering

Cloud platforms

Docker & Kubernetes

Data engineering

Distributed systems

Education

Bachelor's or Master's in CS/IT/Engineering/Data Science

Tools

Docker

Kubernetes

Spark

Kafka

LLMs

Job description

• Lead the architecture, design, and development of scalable enterprise technology solutions.
  
• Drive the development and deployment of AI/ML and GenAI solutions, including LLMs, RAG, vector databases, AI agents, and model orchestration.
  
• Provide technical leadership across software engineering, APIs, microservices, distributed systems, and data platforms.
  
• Design cloud-native solutions using AWS, Azure, or GCP, ensuring scalability, security, and performance.
  
• Drive CI/CD, DevOps, containerization, and deployment practices using Docker and Kubernetes.
  
• Oversee data engineering solutions involving data pipelines, ETL/ELT, Spark, Kafka, and cloud data platforms.
  
• Conduct architecture and code reviews, establish engineering standards, and resolve complex technical issues.
  
• Lead, mentor, and develop engineering teams while promoting best practices and continuous improvement.
  
• Collaborate with business stakeholders and cross-functional teams to translate business requirements into technical solutions.
  
• Ensure production readiness, system reliability, responsible AI practices, and continuous performance monitoring.

Requisites

• Bachelor's or Master's degree in Computer Science, IT, Engineering, Data Science, or a related field.
  
• Strong background in software engineering, AI/ML engineering, data engineering, or related technology domains.
  
• Experience in technical leadership, architecture, and engineering team management.
  
• Solid understanding of software architecture, design patterns, APIs, microservices, and distributed systems.
  
• Hands-on experience with AI/ML, GenAI, LLMs, RAG, or related AI technologies.
  
• Strong experience with at least one major cloud platform: AWS, Azure, or GCP.
  
• Hands-on knowledge of Docker, Kubernetes, CI/CD, and DevOps practices.
  
• Good understanding of databases, data architecture, and data engineering fundamentals.
  
• Experience delivering production-grade enterprise applications and working with Agile/Scrum methodologies.
  
• Strong problem-solving, debugging, architecture, and technical decision-making skills.
  
• Excellent communication, stakeholder management, mentoring, and team coordination skills.
  
• Ability to balance hands-on engineering, architecture, team leadership, and stakeholder-facing responsibilities.