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Principal AI Engineer

MorningstarNavi Mumbai, Maharashtra, IndiaPosted 19 May 2026

As a Principal AI Engineer at Morningstar, you will define the technical direction for production-grade AI systems, focusing on LLM inference platforms, orchestration, and resilient data pipelines. You will architect scalable solutions, manage AI cost governance, and lead engineering best practices across the platform ecosystem. The role requires expert Python proficiency, deep experience with AWS and cloud-native infrastructure, and a track record of deploying LLMs at scale. This position is a high-level IC role focused on architectural leadership and system reliability within a hybrid work model.

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Experience

9+ years

Function

Engineering

Work mode

Hybrid, India

Company

Tier 2

What you will work on

As a Principal AI Engineer at Morningstar, you will define the technical direction for production-grade AI systems, focusing on LLM inference platforms, orchestration, and resilient data pipelines. You will architect scalable solutions, manage AI cost governance, and lead engineering best practices across the platform ecosystem. The role requires expert Python proficiency, deep experience with AWS and cloud-native infrastructure, and a track record of deploying LLMs at scale. This position is a high-level IC role focused on architectural leadership and system reliability within a hybrid work model.

TAL's take

Quality 65/1005/5 clarityTier 2 company

Solid role at a well-known financial data firm with high technical seniority requirements and clear architectural scope, but the company tier is mid-market.

The JD is extremely detailed, outlining specific technical responsibilities, infrastructure stack, and expectations for the Principal role.

Salaries at Morningstar

10.8 LPA average

Based on 23 Grapevine salary entries for Morningstar.

View all salaries

Engineering

2 - 4 years | L2

8 LPA average

Range: 8 - 9 LPA

Engineering

4 - 6 years | L1

9 LPA average

Range: 9 - 9 LPA

Engineering

6 - 8 years

20 LPA average

Range: 20 - 20 LPA

Engineering

10 - 12 years | L1

22 LPA average

Range: 22 - 22 LPA

Must haves

  • 9+ years of experience in AI engineering or MLOps
  • Expert-level programming in Python
  • Proven experience deploying and operating LLMs in production at scale
  • Strong knowledge of AWS, cloud-native design, and distributed systems
  • Experience with container orchestration and infrastructure automation

Tools and skills

pythonawskubernetesterraformpostgresqlllmmlops

Nice to have: javascript, typescript, cloudwatch, prometheus, grafana.

About the company

Established financial research and data company, strong market presence but not a top-tier global or India-specific pure-tech brand.

Posts mentioning Morningstar