Job Title: AWS AI Engineer

Budget: 2 LPM

Work Hours: 4:30 PM to 1:30 AM

Key Responsibilities:

• Design and deploy GenAI and traditional AI solutions using advanced techniques and AWS infrastructure.

• Develop and expose APIs using AWS services. Rapidly prototype proof-of-concept AI solutions.

• Handle and process data from diverse sources, including spreadsheets, SQL databases, APIs, and S3.

• Communicate complex technical concepts clearly to senior stakeholders.

Technical Expertise

• Generative AI & Machine Learning:

Prompt Engineering, Agent-based Architectures, RAG, Transformer Architectures. Fine-tuning LLMs, Model Optimisation, Deployment Strategies on AWS. LangChain or similar frameworks. AWS Bedrock – Mandatory with High Expertise.

• Traditional AI/ML Techniques:

Regression, Classification, Clustering, Ensemble Methods, Dimensionality Reduction, Anomaly Detection. Neural Networks: ANNs, CNNs, RNNs, LSTMs, GRUs, Transformers, GANs, VAEs. Reinforcement Learning. Strong foundation in Linear Algebra, Calculus, and Statistics.

• Development & Deployment:

API development using AWS API Gateway, Lambda, RDS, DynamoDB, Redis, and Route 53. Infrastructure as Code: AWS CDK or CloudFormation Templates. CI/CD: CodeDeploy, CodeBuild.

• Programming & Tools:

Python and ML libraries: Scikit-learn, TensorFlow, Keras, PyTorch, MXNet, XGBoost. Ethical AI: Fairness, Explainability, Transparency, Societal Impact.

Experience & Qualifications: 8+ years of experience implementing enterprise AI projects. Proven ability to deliver real-world AI solutions. Excellent communication and articulation skills.