Lead AWS AI/ML Engineer

Company Overview :

I2K2 Networks (P) Limited is a premier IT infrastructure and managed services provider, specializing in cloud computing, data center management, and enterprise-grade security solutions. Operating at the intersection of high-performance infrastructure and emerging technology, the company empowers businesses to scale their digital operations through robust cloud architectures. With a focus on delivering reliable, secure, and scalable environments, I2K2 supports a diverse portfolio of clients across various sectors, ensuring seamless digital transformation and operational excellence.

Job Description :

We are seeking an experienced AWS AI & Machine Learning Lead with at least 5 years in a leadership role.

The ideal candidate should possess strong expertise in AWS AI & Machine Learning services and have the ability to work independently while effectively leading and mentoring a team.

Key Responsibilities :

- Architect and deploy end-to-end machine learning pipelines on AWS to streamline model development and production readiness.

- Integrate advanced Gen AI services and large language models into existing client platforms to automate workflows and improve user experiences.

- Lead the implementation of MLOps practices to ensure continuous integration, deployment, and monitoring of AI models at scale.

- Collaborate with data engineering teams to build robust data pipelines that feed high-quality, structured data into AI models.

- Mentor junior engineers and technical staff on best practices for cloud-native AI development and infrastructure optimization.

- Evaluate emerging AI technologies and frameworks to maintain the company's competitive advantage in the cloud services market.

Key skills and experience required :

- AWS AI & Machine Learning

- Generative AI

- Machine Learning (experience in model building is an added advantage; however, hands-on expertise in designing and managing MLOps pipelines is mandatory)

- AWS AI Services

- Cloud Architecture

- Data Engineering

- MLOps & DevOps

- Programming and Software Development

- End-to-end AI/ML solution design and implementation

- The candidate should have a proven track record of delivering scalable AI/ML solutions, driving technical excellence, and leading teams in a fast-paced, cloud-native environment.

AWS AI & Machine Learning :

Generative AI :

- Amazon Bedrock

- Bedrock Agents

- Bedrock Knowledge Bases

- Model Customization

- Prompt Engineering

- RAG Architecture

- Multi-Agent Systems

- AI Guardrails

Machine Learning (building model is an addon but mlops pipeline is compulsory) :

- Amazon SageMaker

- SageMaker Pipelines

- Feature Store

- Model Training & Deployment

- Hyperparameter Tuning

- Model Monitoring

AI Services :

- Amazon Textract

- Amazon Comprehend

- Amazon Rekognition

- Amazon Transcribe

- Amazon Translate

- Amazon Polly

- Amazon Lex

- Amazon Kendra

Cloud Architecture :

- AWS Well-Architected Framework

- Multi-Account Architecture

- IAM & Security

- VPC Design

- API Gateway

- Lambda

- ECS

- EKS

- Step Functions

- EventBridge

Data Engineering :

- Amazon S3

- Glue

- Athena

- Redshift

- DynamoDB

- RDS

- Aurora

- Kinesis

- Kafka

- Data Lakes

- Data Warehousing

MLOps & DevOps :

- CI/CD for ML

- SageMaker Pipelines

- Docker

- Kubernetes

- MLflow

- Model Registry

- Monitoring & Observability

Programming :

- Python

- SQL

- PySpark

- FastAPI

- Streamlit

- LangChain

- LangGraph