Tech Lead – AI & Engineering
Master Mind Consultancy (company site, opens in a new tab)10–15 yrsChennaiOn-siteDirect career pageEst. 30–55 LPA
Posted 15h ago
Reach people at Master Mind Consultancy
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Master Mind Consultancy you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead architecture, design, and development of scalable AI/ML and enterprise technology solutions, including GenAI technologies like LLMs, RAG, vector databases, and model orchestration.
- Provide technical leadership in software engineering across cloud-native solutions on AWS, Azure, or GCP, microservices, distributed systems, CI/CD, DevOps, and data engineering pipelines.
- Lead and mentor engineering teams, conduct architecture and code reviews, ensure production readiness, system reliability, and collaborate with business stakeholders to translate requirements into technical solutions.
Minimum Requirements
- 10 to 15 years of professional experience in software engineering and technical leadership roles.
- Bachelor's or Master's degree in Computer Science, IT, Engineering, Data Science, or related field.
- Hands-on experience with AI/ML, GenAI, LLMs, RAG and cloud platforms (AWS, Azure, or GCP).
- Proficiency in Python, Java, JavaScript/TypeScript, or C++ and expertise in Docker, Kubernetes, CI/CD, microservices, APIs, and distributed systems.
Ideal Candidate Profile
- Experienced tech leader with proven ability to architect and deploy enterprise-grade AI/ML solutions using modern cloud technologies.
- Strong practical expertise in managing cross-functional engineering teams while balancing hands-on development and strategic architecture decisions.
- Skilled in delivering production-ready software with deep knowledge of DevOps, data engineering, and scalable distributed systems.