Role Overview :

We are looking for a Senior / Lead AI Engineer to design, build, and scale production-grade AI systems.

This role combines hands-on AI engineering with system architecture leadership. The candidate will be responsible for designing scalable AI platforms, mentoring engineers, and ensuring that machine learning models are successfully deployed into real-world applications.

The ideal candidate has strong expertise in machine learning, backend engineering, distributed systems, and modern LLM ecosystems, along with experience designing scalable AI architectures.

Key Responsibilities :

AI System Architecture :

- Design scalable architectures for AI-powered products and services

- Architect end-to-end ML systems including training, deployment, and monitoring

- Define architectural standards for AI services, APIs, and data pipelines

- Design distributed AI systems that support large-scale inference and data processing

AI Engineering & Development :

- Build and deploy production AI/ML systems

- Develop APIs and services exposing AI capabilities

- Implement LLM-powered systems including :

- RAG pipelines

- Semantic search

- Conversational AI systems

- Optimize model performance, latency, and scalability

AI Platform & Infrastructure :

- Design and maintain ML infrastructure for training and deployment

- Build scalable inference systems for ML and LLM models

- Implement CI/CD pipelines for ML systems

- Deploy services using containerized infrastructure

Technical Leadership :

- Lead AI engineering teams and mentor junior engineers

- Conduct architecture and code reviews

- Define engineering standards for AI development

- Guide teams in implementing scalable AI solutions

Cross-Team Collaboration :

- Work closely with product and engineering leadership

- Translate business problems into scalable AI solutions

- Coordinate with data engineering, backend, and platform teams

Required Skills :

Programming & Software Engineering :

- Expert-level Python

- Strong experience writing production-grade systems

- Experience designing scalable backend services

Machine Learning & AI :

- Strong experience with :

- Supervised and unsupervised learning

- Model evaluation and optimization

- Feature engineering

- Model deployment pipelines

- Experience with :

- PyTorch / TensorFlow

- Scikit-learn

LLM & Modern AI Stack :

- Experience with :

- LLM APIs (OpenAI, Claude, etc.)

- RAG architectures

- LangChain / LlamaIndex

- Embedding models and semantic search

- Prompt engineering and LLM orchestration

Databases :

- Experience working with :

- PostgreSQL

- MongoDB

- Vector databases (Pinecone, Weaviate, FAISS, Chroma)

Infrastructure & Deployment :

- Docker

- Kubernetes (preferred)

- Cloud platforms (AWS / GCP / Azure)

- CI/CD pipelines

System Architecture :

- Experience designing :

- Distributed AI systems

- Microservices architectures

- Data pipelines and ML workflows

- High-performance inference systems

Ideal Candidate Profile :

- 10+ years experience in AI / ML / Backend engineering

- Experience designing AI system architectures

- Experience leading AI engineering teams

- Strong problem-solving and system design skills

- Experience building production AI products at scale

What We Are NOT Looking For :

- Profiles focused only on research or academic ML

- Candidates who primarily worked in notebooks without production deployment experience

- Engineers without strong software engineering fundamentals