Lead AWS AI/ML Engineer
First seen by Alion on Jul 24, 2026.
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
Skills
AWS, Artificial Intelligence, Machine Learning, Generative AI, MLOps, Prompt Engineering, Python