Lead AI Engineer

Clair Labs; Bengaluru; On-site; INR 4,500,000 - 6,500,000; Full time

Job summary

Clair Labs in Bengaluru is seeking a Lead AI Engineer to design, build, and deploy scalable AI-powered applications. You will lead the AI engineering lifecycle, mentor engineers, and ensure robust backend APIs.

The role emphasizes hands-on Python backend development, Generative AI, LLMs, and cloud deployment with Docker/Kubernetes and CI/CD. A senior, technically strong candidate is sought.

Qualifications

• 7–10 years in software/AI engineering with strong Python backend experience.
• Hands-on AI/ML development and deployment, production-grade APIs.
• Experience with scalable microservices and cloud deployments.
• Familiarity with LLMs, NLP, and modern AI tooling.

Responsibilities

• Design, develop, and deploy scalable AI/ML solutions for business use cases.
• Integrate AI/ML models into production backend services and APIs.
• Lead AI engineering initiatives from architecture to production deployment.
• Mentor engineers and enforce best practices across teams.
• Work with AWS/Azure/GCP, Docker, Kubernetes, and CI/CD pipelines.

Skills

Python

Python Backend Development

REST APIs

FastAPI Flask Django

Artificial Intelligence ML

Generative AI LLM

Microservices Architecture

API Development Integration

SQL NoSQL Databases

Git Version Control

Cloud AWS Azure GCP

Docker Containerization

Software Engineering Best Practices

Education

Bachelor's or Master's in CS/Engineering/AI/ML/Data Science

Tools

LangChain

LangGraph

LlamaIndex

Pinecone

FAISS

Weaviate

Milvus

OpenAI Gemini Claude Llama APIs

Kubernetes

CI/CD

Kafka

Job description

We are looking for an experienced and technically strong Lead AI Engineer to join our engineering team in Bangalore. The ideal candidate will have 7-10 years of experience in software engineering and AI/ML, with strong hands-on expertise in Python backend development and Artificial Intelligence. The candidate will be responsible for designing, developing, and deploying scalable AI-powered applications and services. This role requires someone who can work across the complete AI engineering lifecycle, from developing AI/ML solutions and integrating models into applications to building robust backend APIs and production-ready systems. The ideal candidate should have strong programming fundamentals, hands-on experience with Python as a backend technology, and the ability to lead technical initiatives while mentoring engineers.

The candidate will have responsibilities across the following functions:

AI and Machine Learning Engineering:

• Design, develop, and deploy scalable AI/ML solutions for business and product use cases.
• Build and integrate machine learning and AI models into production applications.
• Work with Generative AI, LLMs, NLP, Machine Learning, and Deep Learning technologies.
• Evaluate different AI/ML models and select appropriate approaches based on business requirements.
• Develop production-ready AI pipelines and model-serving solutions.
• Optimise AI systems for performance, scalability, reliability, and cost.

Python Backend Development:

• Strong hands-on experience with Python backend development is mandatory.
• Design and develop scalable backend services using Python.
• Build robust REST APIs and microservices using frameworks such as FastAPI, Flask, or Django.
• Integrate AI/ML models with backend applications and enterprise systems.
• Develop secure, maintainable, well-tested, and high-performance backend services.
• Work with databases, caching systems, message queues, and external APIs.
• Troubleshoot and optimise backend applications for scalability and performance.

Generative AI and LLM:

• Develop applications using Large Language Models (LLMs).
• Work with RAG (Retrieval-Augmented Generation) architectures and AI-powered applications.
• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies is preferred.
• Work with prompt engineering, embeddings, vector databases, and model orchestration.
• Integrate commercial and/or open-source AI models into production systems.
• Implement evaluation, monitoring, and optimisation strategies for AI applications.

Technical Leadership:

• Lead AI engineering initiatives from architecture and development through production deployment.
• Provide technical guidance and mentorship to junior and senior engineers.
• Conduct code reviews and establish engineering best practices.
• Make architecture and technology decisions for AI and backend systems.
• Collaborate with Product Managers, Data Scientists, ML Engineers, Software Engineers, and other stakeholders.
• Translate business requirements into scalable technical solutions.
• Identify new AI technologies and evaluate their potential business applications.

Cloud and Deployment:

• Design and deploy AI/backend applications on cloud platforms such as AWS, Azure, or GCP.
• Work with Docker, Kubernetes, CI/CD pipelines, and cloud-native architectures.
• Implement monitoring, logging, security, and observability for production AI systems.
• Ensure AI services are scalable, reliable, and production-ready.

Requirements:

• 7-10 years of overall software/AI engineering experience.
• Strong professional experience developing applications using Python.
• Proven experience in Python backend development.
• Hands-on experience building and deploying AI/ML solutions.
• Experience developing scalable APIs and microservices.
• Experience working with production-grade software systems.
• Prior experience in a technical leadership or lead engineering capacity is preferred.
• Experience working with cross-functional engineering and product teams.
• Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical discipline.
• Strong programming and software engineering fundamentals are essential.
• Key Skills / ATS Keywords: Lead AI Engineer: AI Engineer, Artificial Intelligence, Generative AI, GenAI, LLM, Machine Learning, Python, Python Backend, FastAPI, Flask, Django, REST API, Microservices, RAG, LangChain, LangGraph, LlamaIndex, NLP, Deep Learning, PyTorch, TensorFlow, Vector Database, AWS, Azure | GCP, Docker, Kubernetes, MLOps, AI Agents, Agentic AI, Prompt Engineering, API Development, Backend Engineering, System Design.

Mandatory Skills:

The candidate should have strong hands-on experience in:

• Python - Mandatory
• Python Backend Development - Mandatory
• REST APIs
• FastAPI / Flask / Django
• Artificial Intelligence / Machine Learning
• Generative AI / LLM
• Microservices Architecture
• API Development & Integration
• SQL and/or NoSQL Databases
• Git and Version Control
• Cloud Platforms - AWS / Azure / GCP
• Docker / Containerization
• Software Engineering Best Practices

Good to Have:

• LangChain / LangGraph / LlamaIndex
• RAG
• Vector Databases - Pinecone, FAISS, Weaviate, Milvus, etc.
• Prompt Engineering
• OpenAI / Gemini / Claude / Llama or other LLM APIs
• NLP
• Deep Learning
• PyTorch / TensorFlow
• ML Model Deployment & MLOps
• Kubernetes
• CI/CD
• Kafka or other messaging systems
• AI Agents / Agentic AI
• Model evaluation and observability

Nice to Have:

We are looking for someone who:

• Is a hands-on AI Engineer, rather than purely a people manager.
• Has strong Python backend development experience.
• Can independently design and implement AI-powered applications.
• Understands both AI/ML concepts and production software engineering.
• Can take ownership of complex technical problems.
• Has strong system-design and architectural thinking.
• Can mentor engineers and drive technical excellence.
• Is comfortable working in a fast-paced, collaborative environment.