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Lead - DAML Delivery

Quadrasystems.net India Private Limited | AWS SBU - 2026

Role Overview

The Lead - DAML Delivery is a senior technical and delivery leadership role responsible for end-to-end ownership of Data Analytics and Machine Learning (DAML) engagements within the AWS Strategic Business Unit (SBU). You will lead a team of data and ML engineers, define technical architecture for client solutions, and ensure delivery excellence from presales through production deployment. This role combines hands-on architecture, stakeholder management, and team mentorship.

Key Responsibilities

Delivery Leadership

- Own the end-to-end delivery lifecycle for DAML client engagements, including requirements gathering, architecture design, testing, deployment, and hypercare.
- Lead sprint planning, technical reviews, and delivery governance across concurrent projects.
- Manage client relationships as the primary technical point of contact, presenting architecture decisions, managing expectations, and resolving escalations.
- Produce and review technical documentation, including architecture decision records, solution designs, and runbooks.

Technical Architecture

- Architect enterprise-scale data platforms on AWS, such as data lakes on S3 with Lake Formation, warehousing on Amazon Redshift, and real-time analytics with Kinesis and Apache Flink on Amazon MSK.
- Design ML pipelines on Amazon SageMaker, covering data preparation, model training, hyperparameter optimization, deployment, and monitoring.
- Define integration patterns between data platforms and Agentic AI architectures, including RAG pipelines,



feature stores, and model-serving endpoints.
- Conduct AWS Well-Architected Framework reviews for data and ML workloads, evaluating reliability, performance efficiency, cost optimization, and security.
- Lead technical presales activities, including solution scoping, effort estimation, and proof-of-concept design for current client opportunities.

Team Development

- Mentor and guide a team of 3-6 data and ML engineers through code reviews, architecture walkthroughs, and capability development plans.
- Define engineering standards, coding conventions, and reusable accelerators for the DAML practice.
- Evaluate and adopt emerging AWS data and AI capabilities, staying ahead of the roadmap to create client value.

Technical Skills Required

AWS Data & ML Services (Expert Level)

- Amazon SageMaker: training, inference, pipelines, Model Monitor, Feature Store
- Amazon Redshift, Amazon Athena, AWS Glue, Amazon EMR, Amazon MSK
- Amazon Kinesis, AWS DMS, Amazon S3, AWS Lake Formation
- Amazon Bedrock: foundation models, RAG integration with DAML architectures
- Amazon QuickSight, AWS Step Functions, AWS Lambda

Underlying Technologies (Expert Level)

- Machine Learning: supervised/unsupervised learning, ensemble methods, neural networks, NLP
- Python: pandas, scikit-learn, TensorFlow, PyTorch,



XGBoost
- MLOps: experiment tracking (MLflow), model versioning, A/B testing, drift detection
- SQL (advanced), Apache Spark, dbt for data transformation
- Feature engineering, model evaluation metrics, and production ML monitoring
- Data architecture patterns: Lambda/Kappa architectures, Medallion architecture (Bronze/Silver/Gold)
- GenAI and LLM concepts: prompt engineering, fine-tuning, RAG, evaluation frameworks

Good to Have

- AWS Certified Machine Learning - Specialty
- AWS Certified Data Analytics - Specialty
- Experience with MLflow, Kubeflow, or similar MLOps platforms
- Familiarity with Agentic AI patterns and Amazon Bedrock Agents

Qualifications

- Bachelor s or Master s degree in Computer Science, Data Science, Machine Learning, or a related quantitative field
- 5+ years of progressive experience in data engineering, data science, or ML engineering roles
- Demonstrated track record of leading technical delivery teams and managing client relationships in a consulting or professional services environment

Why Quadrasystems

This is a senior leadership role with direct impact on Quadrasystems AWS SBU growth and client outcomes. You will shape the architecture of enterprise data and AI platforms, build the DAML practice from within, and be at the forefront of applying Agentic AI to real business problems at scale. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Lead - DAML Delivery (Bengaluru)
🏢 Quadrasystems.Net
📍 Bengaluru