Job
Description
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ready to join immediately
can share their details via email for quick processing.
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CCTC | ECTC | Notice Period | Location Preference
nitin.patil@ust.com
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Roles and Responsibilities:
Architecture & Infrastructure Design
Architect scalable, resilient, and secure AI/ML infrastructure on AWS using services like
EC2, SageMaker, Bedrock, VPC, RDS, DynamoDB, CloudWatch
.
Develop Infrastructure as Code (IaC) using
Terraform
, and automate deployments with
CI/CD pipelines
.
Optimize cost and performance of cloud resources used for AI workloads.
AI Project Leadership
Translate business objectives into actionable AI strategies and solutions.
Oversee the
entire AI lifecycle
—from data ingestion, model training, and evaluation to deployment and monitoring.
Drive roadmap planning, delivery timelines, and project success metrics.
Model Development & Deployment
Lead selection and development of AI/ML models, particularly for
NLP, GenAI, and AIOps use cases
.
Implement frameworks for
bias detection, explainability
, and
responsible AI
.
Enhance model performance through tuning and efficient resource utilization.
Security & Compliance
Ensure data privacy, security best practices, and compliance with
IAM policies, encryption standards
, and regulatory frameworks.
Perform regular audits and vulnerability assessments to ensure system integrity.
Team Leadership & Collaboration
Lead and mentor a team of cloud engineers, ML practitioners, software developers, and data analysts.
Promote cross-functional collaboration with business and technical stakeholders.
Conduct technical reviews and ensure delivery of production-grade solutions.
Monitoring & Maintenance
Establish robust model
monitoring
,
ing
, and
feedback loops
to detect drift and maintain model reliability.
Ensure ongoing optimization of infrastructure and ML pipelines.
Must-Have Skills:
10+ years of experience in IT with 4+ years in AI/ML leadership roles.
Strong hands-on experience in
AWS services
: EC2, SageMaker, Bedrock, RDS, VPC, DynamoDB, CloudWatch.
Expertise in
Python
for ML development and automation.
Solid understanding of
Terraform, Docker, Git
, and
CI/CD pipelines
.
Proven track record in delivering AI/ML projects into
production environments
.
Deep understanding of
MLOps, model versioning, monitoring
, and
retraining pipelines
.
Experience in implementing
Responsible AI
practices – including fairness, explainability, and bias mitigation.
Knowledge of
cloud security best practices
and IAM role configuration.
Excellent leadership, communication, and stakeholder management skills.
Good-to-Have Skills:
AWS Certifications
such as AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect.
Familiarity with
data privacy laws and frameworks
(GDPR, HIPAA).
Experience with
AI governance and ethical AI
frameworks.
Expertise in
cost optimization
and performance tuning for AI on the cloud.
Exposure to
LangChain
,
LLMs
,
Kubeflow
, or
GCP-based AI services
.
Skills
Enterprise Architecture,Enterprise Architect,Aws,Python
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