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Primetrace Technologies
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System Engineer (Data, AI Workflows & Platform Reliability), VP

System Engineer (Data, AI Workflows & Platform Reliability), VP

Primetrace Technologies

10 - 15 years

35 - 40 Lacs

Gurugram

Posted:1 week ago| Platform:

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Skills Required

Computer science Automation Data validation Formulation Data collection Healthcare Workflow Downstream SQL Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

About this role

Role Summary:

We re seeking a dynamic System Engineer to design and deliver intelligent, scalable, and reliable data systems. This hybrid role combines data engineering, AI/ML integration, system reliability, and DevOps to accelerate data collection, enable intelligent workflows, and drive business impact. You ll collaborate across engineering, data analytics, and business teams to build reusable frameworks, reduce time-to-value, and uphold engineering excellence.

Key Responsibilities:

Data & AI Workflow Engineering

Accelerate data collection at scale from millions of sources using robust, scalable pipelines.
Design, build, and deploy workflows that combine AI/ML models with human-in-the-loop systems.
Operate as a full-stack data engineer , taking projects from problem formulation to production.
Develop APIs and services to expose data and model outputs for downstream consumption.

System Engineering, Reliability & DevOps

Build and maintain CI/CD pipelines for data and ML services using Azure DevOps or GitHub Actions.
Implement observability (metrics, logs, traces) and reliability features (retries, circuit breakers, graceful degradation).
Optimize data workflows and infrastructure for performance, scalability, and fault tolerance .
Lead incident response, root cause analysis, and postmortems for data and ML systems.
Contribute to infrastructure-as-code (IaC) for provisioning and managing cloud-native environments.

Platform & Framework Development

Elevate development standards through reusable services, frameworks, templates, and documentation.
Champion best practices in code quality, security, and automation across the engineering lifecycle.
Collaborate with engineering teams across the business to improve time-to-value and share internal solutions.

Collaboration & Business Impact

Collaborate with stakeholders, ensure that risks are mitigated timely and drive through metrices.
Collaborate with engineering teams across the business to improve time-to-value and share internal solutions.
Translate business problems into data science/ML solutions with measurable outcomes.
Propose pragmatic, diverse approaches to solving business challenges using data and AI.
Present results and recommendations clearly to technical and non-technical audiences using compelling storytelling and visualizations.

Required Skills and Qualifications:

10+ years of experience in data engineering , machine learning , or system/platform engineering .
Strong programming skills in Python/DotNet or Java ; proficiency in SQL , DBT , and data orchestration tools (e.g., Airflow).
Experience with containerization (Docker) and Kubernetes on Azure and/or AWS.
Proficiency in CI/CD , Git , and cloud-native development .
Familiarity with observability tools (Azure Monitor, Prometheus, Grafana) and data validation frameworks (e.g., Great Expectations).
Familiarity with data science libraries (Pandas, NumPy, scikit-learn) and deploying ML models to production.
Strong understanding of distributed systems , microservices , and API design .
Excellent communication and stakeholder engagement skills.
Bachelor s or Master s degree in Computer Science, Data Science, Engineering, or a related field.

Our benefits
.

Our hybrid work model

BlackRock s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

This mission would not be possible without our smartest investment the one we make in our employees. It s why we re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com / company / blackrock

BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, family status, gender identity, race, religion, sex, sexual orientation and other protected attributes at law.

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System Engineer (Data, AI Workflows & Platform Reliability), VP