Overview

🚀 Hiring: Senior Generative AI Engineer – Python, LangChain, RAG & AWS

Responsibilities

• Build LLM-powered applications and Retrieval-Augmented Generation (RAG) solutions using LangChain and AWS Bedrock.
• Develop, fine-tune, evaluate, and deploy machine learning models using TensorFlow, PyTorch, scikit-learn, and NumPy.
• Work on NLP and computer vision use cases, integrating pre-trained models where appropriate.
• Optimise AI solutions for performance, scalability, and efficiency.
• Develop RESTful APIs using FastAPI or Flask.
• Build secure, scalable microservices and integrate AI capabilities into applications.
• Test and validate APIs using Postman.
• Deploy and manage AI workloads using AWS Bedrock, S3, Lambda, SageMaker, ECS/EKS, and IAM.
• Integrate event-driven workflows using SNS, SQS, and API Gateway.
• Support CI/CD pipelines, Docker-based deployments, and Kubernetes orchestration.
• Manage cloud security, infrastructure provisioning, and cost optimisation.
• Implement vector storage and retrieval using PostgreSQL and pgvector.
• Work with relational and NoSQL databases, including MySQL, DynamoDB, and MongoDB.
• Build and automate ETL workflows and data pipelines using Airflow, AWS Glue, or Spark.
• Collaborate with data scientists, engineers, and product managers.
• Document models, APIs, workflows, and deployment processes.
• Communicate technical concepts clearly to non-technical stakeholders.
• Strong Python programming skills, with knowledge of OOP and microservices architecture.
• Hands-on experience with LLMs, RAG, AWS Bedrock, and the mandatory technologies listed above.
• Experience with AI/ML frameworks, cloud deployments, databases, and data pipelines.
• Familiarity with Git-based collaboration and tools such as Jira or Trello.
• Strong analytical, problem-solving, communication, and teamwork skills.

Qualifications

• LangChain
• AWS Lambda, AWS Bedrock,SNS, SQS, and API Gateway
• FastAPI
• PostgreSQL with pgvector
• Postman
• Git