AI Tech Lead

AI Tech Lead

Company: Capticks
Experience: 5+ Years
Employment Type: Full-time
Work Mode: Remote
Location: India

Job Summary :

Capticks is looking for a highly experienced AI Tech Lead with strong expertise in AI/ML Engineering, Generative AI, LLMs, and production-grade AI systems.

The ideal candidate should not only understand AI/ML concepts but also have hands-on experience building, deploying, monitoring, and maintaining reliable AI/ML solutions in real-world production environments.

The candidate must stay up to date with modern, reliable, and widely adopted industry practices for developing production-level AI systems and should be capable of making sound technical and architectural decisions.

Key Responsibilities

• Lead the architecture, development, deployment, and optimization of AI/ML systems.
• Design and build production-ready solutions using Machine Learning, Deep Learning, Generative AI, LLMs, and Agentic AI.
• Develop scalable AI services, pipelines, and APIs using Python and modern backend frameworks.
• Design and implement RAG pipelines, AI agents, multi-step workflows, embeddings, vector search, and LLM applications.
• Evaluate AI/ML models based on accuracy, latency, scalability, reliability, cost, and production performance.
• Establish and follow production-grade AI/ML engineering practices, including testing, evaluation, monitoring, observability, versioning, security, and deployment.
• Select appropriate models, frameworks, infrastructure, and architecture based on business and technical requirements.
• Design systems capable of handling real-world production workloads, failures, model changes, and scaling requirements.
• Implement appropriate approaches for model evaluation, prompt evaluation, hallucination reduction, data quality, and AI system reliability.
• Lead technical discussions, architecture reviews, code reviews, and engineering standards.
• Mentor AI/ML engineers and developers and provide technical direction.
• Work closely with product and engineering teams to convert business requirements into scalable AI solutions.
• Continuously evaluate emerging AI technologies and determine their practical applicability and production readiness.

Mandatory Technical SkillsAI/ML Engineering

• Strong understanding of Machine Learning and AI/ML engineering principles.
• Hands-on experience developing and deploying production AI/ML systems.
• Strong understanding of model development, evaluation, experimentation, inference, and optimization.
• Experience with Python and relevant AI/ML libraries and frameworks.
• Understanding of ML lifecycle, model versioning, data pipelines, model monitoring, and deployment.

Generative AI & LLMs

• Strong practical knowledge of Generative AI and Large Language Models (LLMs).
• Experience with RAG, embeddings, vector databases, semantic search, prompt engineering, and tool/function calling.
• Experience building reliable LLM-powered applications and AI agents.
• Understanding of LLM evaluation, hallucination mitigation, context management, latency, token optimization, and cost optimization.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent technologies.

Production Engineering

The candidate must have a strong understanding of production-level AI engineering practices, including:

• AI/ML system architecture
• Model and prompt versioning
• Automated testing and evaluation
• Data and model validation
• Monitoring and observability
• Logging and tracing
• Model performance monitoring
• CI/CD for AI/ML applications
• Docker and containerization
• Cloud deployment
• Scalability and high availability
• Security and access control
• Cost and latency optimization
• Failure handling and fallback strategies
• Responsible and reliable AI practices

Leadership & Architecture

• 5+ years of professional software/AI engineering experience.
• Ability to independently own AI system architecture and technical decisions.
• Experience mentoring engineers and conducting technical reviews.
• Strong understanding of microservices, distributed systems, APIs, databases, and cloud architecture.
• Ability to evaluate new AI technologies critically rather than adopting tools solely because they are trending.
• Strong communication and problem-solving skills.

Strongly Preferred

• Experience with **Agentic AI and …