Senior AI Engineer

JOB DESCRIPTION:

Key Responsibilities

• Build and deploy AI/ML applications using LLMs and traditional ML models
• Design and implement RAG pipelines, semantic search, embeddings, and vector database integrations
• Develop scalable backend services and APIs for AI products
• Build microservices for model serving, inference orchestration, and workflow automation
• Design feature engineering pipelines, data preprocessing, and model training systems
• Implement MLOps practices including CI/CD, model monitoring, drift detection, and automated retraining
• Build observability for AI systems including latency, usage, and quality monitoring
• Deploy AI workloads using cloud-native tools and container orchestration
• Collaborate with product, engineering, and data teams to ship AI features into production

Required Skills

AI / GenAI

• Experience with LLM application development
• Strong knowledge of RAG, embeddings, prompt engineering, and fine-tuning
• Hands-on experience with:
  • LangChain
  • LlamaIndex
  • Hugging Face
• Experience with vector databases:
  • FAISS
  • Pinecone
  • Chroma
• Knowledge of model optimization:
  • LoRA
  • QLoRA
  • quantization
  • vLLM

Backend Engineering

• Strong Python backend development experience
• Hands-on with:
  • FastAPI
  • Flask
• REST API design
• Microservices architecture
• Distributed systems fundamentals
• Async programming
• Caching and queue systems
• Database design and optimization
• API security and authentication
• Production debugging and monitoring

Data & Infrastructure

• SQL and NoSQL databases
• ETL pipelines
• Streaming and batch processing
• Hands-on with:
  • Apache Kafka
  • RabbitMQ
  • Dask

MLOps / Deployment

• Experience with:
  • MLflow
  • Kubeflow
  • Amazon SageMaker
  • Azure Machine Learning
• CI/CD pipelines
• Model monitoring
• A/B testing
• Experiment tracking
• Dockerized deployments

Cloud & DevOps

• Experience with:
  • Amazon Web Services
  • Microsoft Azure
  • Google Cloud
• Hands-on with:
  • Docker
  • Kubernetes
• Production deployment and scaling

Preferred

• Experience in end-to-end AI product development
• Knowledge of knowledge graphs and NLP pipelines
• Experience with model governance and responsible AI
• Strong system design and architecture skills
• Experience building customer-facing AI applications
• Ability to independently own and drive technical initiatives