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Sr Engineer

Job in India, Henry County, Tennessee, USA
Listing for: Target
Full Time position
Listed on 2026-07-08
Job specializations:
  • Software Development
Job Description & How to Apply Below
Location: India

About us:

Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.

As a Senior Engineer, you will lead the design and development of platform-level capabilities for operational intelligence, reliability engineering, and automation across enterprise collaboration ecosystems. You will work on telemetry-driven systems that identify what is unhealthy, why it is happening, and what should be done next - while building automation and architecture that scales across multiple platforms and partners

Key Responsibilities

* Own the design and delivery of critical backend and analytics platform components

* Build scalable telemetry, analytics, and automation systems

* Define operational metrics, health signals, and reliability indicators

* Drive platform evolution from provider-specific analytics to reusable cross-platform capabilities

* Enable reliable operations through engineering guardrails, automation, and data-backed workflows

* Partner cross-functionally with Endpoint Engineering, Device Management, Security, and collaboration platform stakeholders

* Mentor other engineers and raise technical quality across the team

Required Qualifications

* Strong backend engineering experience in Python or similar technologies

* Deep SQL, data processing, and systems design experience

* Experience designing scalable services, APIs, or data-intensive platforms

* Strong problem-solving ability across complex operational systems

* Experience dealing with ambiguity and translating business/operational problems into engineering solutions

Preferred Qualifications

* Experience in observability, telemetry platforms, SRE, reliability engineering, or operational analytics

* Experience with anomaly detection, performance monitoring, and report automation

* Familiarity with enterprise collaboration platforms and their operational signals

* Strong practical understanding of LLM-enabled systems, including:

* model selection for latency vs reasoning

* token/cost optimization

* prompt and response architecture

* evaluation and safety considerations

* production design patterns for AI-assisted workflows
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