AI Technical Lead

Haiintel; Coimbatore District; On-site; INR 1,500,000 - 3,600,000; Full time

Job summary

Haiintel is seeking an experienced AI Tech Lead to head our AI engineering team and shape the design, development, deployment, and scaling of production-grade AI solutions.

The ideal candidate will be a hands-on technical leader with deep expertise in Generative AI, LLMs, RAG, AI Agents, and production AI systems, guiding architecture, mentoring engineers, and collaborating with product and business teams to translate requirements into practical AI applications.

Qualifications

• 712 years of experience in Software Engineering, AI Engineering, ML Engineering, or related fields.
• Experience in a Technical Lead, Lead Engineer, Senior AI Engineer, AI Architect, or similar role.
• Strong hands-on experience building and deploying production-grade AI systems.
• Strong knowledge of Generative AI, LLMs, RAG, embeddings, vector databases, and AI Agents.
• Experience designing agentic workflows and multi-step AI systems.
• Strong understanding of system design, software architecture, and engineering best practices.
• Experience with MLOps/LLMOps, model deployment, evaluation, monitoring, and lifecycle management.
• Strong Python programming and software engineering fundamentals.
• Experience with APIs, microservices, distributed systems, and backend services.
• Knowledge of SQL/NoSQL databases, vector databases, and data pipelines.
• Experience with AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, CI/CD, and cloud deployment.
• Strong debugging, troubleshooting, performance optimization, and root-cause analysis skills.
• Experience working in Agile/Scrum environments.

Responsibilities

• Lead and provide technical direction to the AI engineering team.
• Design and review scalable architectures for AI-powered applications and platforms.
• Build and guide production-grade solutions using LLMs, Generative AI, RAG, AI Agents, and agentic workflows.
• Design AI application architecture, APIs, microservices, data pipelines, model serving, and inference infrastructure.
• Drive AI solutions from POC/prototype to reliable production systems.
• Establish and implement MLOps/LLMOps practices including deployment, versioning, evaluation, monitoring, and lifecycle management.
• Ensure AI systems meet requirements for performance, scalability, reliability, security, and cost efficiency.
• Conduct architecture, code, and technical reviews.
• Mentor AI engineers and help solve complex technical and production challenges.
• Collaborate with DevOps/infrastructure teams for deployment, monitoring, and scaling.
• Work with product and business stakeholders to translate requirements into practical AI solutions.
• Evaluate emerging AI technologies, frameworks, and models and recommend their adoption.

Skills

Generative AI

LLMs

RAG

AI Agents

MLOps/LLMOps

Python

APIs & microservices

Distributed systems

Data pipelines

SQL/NoSQL

Docker

Kubernetes

Cloud platforms (AWS/Azure/GCP)

CI/CD

Agile/Scrum

System design

Problem solving

Mentoring

Leadership

Tools

Docker

Kubernetes

CI/CD

Cloud deployment

Job description

AI Tech Lead

Location: On-site
Experience: 7-12 Years
Employment Type: Full-time
Compensation: 15-36 LPA, based on experience, performance, and overall evaluation

About the Role:

Haiintel is looking for an experienced AI Tech Lead to lead our AI engineering team and drive the design, development, deployment, and scaling of production-grade AI solutions.

The ideal candidate will be a hands-on technical leader with strong experience in Generative AI, LLMs, RAG, AI Agents, AI platforms, and production AI systems. The role involves technical leadership, architecture, hands-on engineering, mentoring, and working closely with engineering, product, and business teams.

Key Responsibilities:

• Lead and provide technical direction to the AI engineering team.
• Design and review scalable architectures for AI-powered applications and platforms.
• Build and guide production-grade solutions using LLMs, Generative AI, RAG, AI Agents, and agentic workflows.
• Design AI application architecture, APIs, microservices, data pipelines, model serving, and inference infrastructure.
• Drive AI solutions from POC/prototype to reliable production systems.
• Establish and implement MLOps/LLMOps practices including deployment, versioning, evaluation, monitoring, and lifecycle management.
• Ensure AI systems meet requirements for performance, scalability, reliability, security, and cost efficiency.
• Conduct architecture, code, and technical reviews.
• Mentor AI engineers and help solve complex technical and production challenges.
• Collaborate with DevOps/infrastructure teams for deployment, monitoring, and scaling.
• Work with product and business stakeholders to translate requirements into practical AI solutions.
• Evaluate emerging AI technologies, frameworks, and models and recommend their adoption.

Required Skills & Qualifications:

• 712 years of experience in Software Engineering, AI Engineering, ML Engineering, or related fields.
• Experience in a Technical Lead, Lead Engineer, Senior AI Engineer, AI Architect, or similar role.
• Strong hands-on experience building and deploying production-grade AI systems.
• Strong knowledge of Generative AI, LLMs, RAG, embeddings, vector databases, and AI Agents.
• Experience designing agentic workflows and multi-step AI systems.
• Strong understanding of system design, software architecture, and engineering best practices.
• Experience with MLOps/LLMOps, model deployment, evaluation, monitoring, and lifecycle management.
• Strong Python programming and software engineering fundamentals.
• Experience with APIs, microservices, distributed systems, and backend services.
• Knowledge of SQL/NoSQL databases, vector databases, and data pipelines.
• Experience with AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, CI/CD, and cloud deployment.
• Strong debugging, troubleshooting, performance optimization, and root-cause analysis skills.
• Experience working in Agile/Scrum environments.

Good to Have:

• Experience building enterprise-grade AI products or SaaS platforms.
• Experience with multi-agent systems and AI orchestration frameworks.
• Experience with model fine-tuning or customization.
• Exposure to AI evaluation, safety, governance, and responsible AI.
• Experience with large-scale data processing and enterprise integrations.
• Cloud, AI, ML, or solution architecture certifications.

Soft Skills:

• Strong technical leadership and architectural decision-making.
• Excellent communication and problem-solving skills.
• Ability to mentor and lead experienced engineers while remaining hands-on.
• Strong ownership and accountability.
• Ability to balance innovation with production reliability and business requirements.
• Ability to work effectively in a fast-paced environment.