Time since we first saw it
Day 26
Similar jobs usually come down between day 6 and day 69.
From 4,347 similar postings that came down. Coming down is not always a hire.
IND Lead Engineer, Data
India GCC-Puppalaguda Village
Live, first seen by us 26 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingBuild conversational AI solutions such as chatbots, virtual assistants, and RAG pipelines
Design business intelligence and semantic layer solutions with dimensional models and metrics
Design and run evaluation and monitoring strategies, including test sets and drift detection
Work with unstructured insurance documents, including parsing, OCR, and PII redaction
Explain technical designs, trade-offs, and risks to technical and non-technical audiences
From the employer’s posting
designing, developing, and deploying conversational AI solutions, including chatbots, virtual assistants, intelligent agents, and Retrieval-Augmented Generation (RAG) pipelines
designing and implementing business intelligence and semantic layer solutions, including dimensional modeling, fact tables, metrics definition
designing and operationalizing evaluation and monitoring strategies, including test set creation (gold and/or synthetic)
Experience working with unstructured data, including document parsing and OCR fundamentals
communicating complex technical designs, trade-offs, evaluation results, and risks to both highly technical and non-technical business audiences
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 9, 202626 days ago
- Recorded sightings
- 73
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
The Hartford is hiring
24 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
- Takes jobs down at a usual pace
- 8% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- SageMaker
- NumPy
- pandas
- PyTorch
- scikit-learn
- TensorFlow
Where the posting names them
We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. • Experience in statistical modeling, machine learning, and advanced analytics using Python, including pandas, NumPy, scikit-learn, and strong SQL for complex data exploration, feature engineering, and knowledge preparation; familiarity with PyTorch and/or TensorFlow preferred. • Experience across the end-to-end modeling and analytics lifecycle, including requirements gathering, experiment design, offline evaluation, and basic production monitoring and validation of AI and BI solutions.
• Experience working with unstructured data, including document parsing and OCR fundamentals, robust text normalization, metadata and lineage awareness, and PII detection or redaction considerations for insurance documents. • Experience working with cloud-based AI and analytics platforms such as Google Vertex AI, AWS SageMaker or Bedrock, or Azure AI Services, supporting experimentation, deployment, and conversational AI use cases. • Experience using Git and Unix-based environments, building reproducible notebooks or pipelines, and applying basic container and cloud concepts to support reliable analytics and AI workflows.
Your next step
Complete your application on thehartford.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Workday
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- Your application status lives in that employer’s Candidate Home, under the same sign-in.
Already applied? Track this application
Has The Hartford posted this job before?
Yes. We’ve followed 2 other IND Lead Engineer, Data jobs there since September 2026. One came down after 48 days. One is still up.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
IND - Lead Engineer, Data - GCC063
We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
• Experience in statistical modeling, machine learning, and advanced analytics using Python, including pandas, NumPy, scikit-learn, and strong SQL for complex data exploration, feature engineering, and knowledge preparation; familiarity with PyTorch and/or TensorFlow preferred.
• Experience across the end-to-end modeling and analytics lifecycle, including requirements gathering, experiment design, offline evaluation, and basic production monitoring and validation of AI and BI solutions.
• Solid understanding and practical application of core machine learning, deep learning, and natural language processing algorithms and architectures.
• Experience designing and implementing business intelligence and semantic layer solutions, including dimensional modeling, fact tables, metrics definition, and operating within data warehouse or data lake environments.
• Experience designing and operationalizing evaluation and monitoring strategies, including test set creation (gold and/or synthetic), defining and tracking metrics such as classification, forecasting, ranking/IR, RAG faithfulness and truthfulness, and customer or operational KPIs, with support for A/B testing and drift detection.
• Experience designing, developing, and deploying conversational AI solutions, including chatbots, virtual assistants, intelligent agents, and Retrieval-Augmented Generation (RAG) pipelines.
• Experience working with unstructured data, including document parsing and OCR fundamentals, robust text normalization, metadata and lineage awareness, and PII detection or redaction considerations for insurance documents.
• Experience working with cloud-based AI and analytics platforms such as Google Vertex AI, AWS SageMaker or Bedrock, or Azure AI Services, supporting experimentation, deployment, and conversational AI use cases.
• Experience using Git and Unix-based environments, building reproducible notebooks or pipelines, and applying basic container and cloud concepts to support reliable analytics and AI workflows.
• Experience communicating complex technical designs, trade-offs, evaluation results, and risks to both highly technical and non-technical business audiences, translating insights into clear business outcomes and strategy.
• Foundational knowledge of insurance products, processes (including underwriting, claims, and pricing), and regulatory environments, with demonstrated ability to apply analytics and AI solutions within a regulated industry context.
• Experience with advanced NLP and Generative AI capabilities, including embeddings, hybrid and dense retrieval strategies, advanced chunking, prompt engineering, structured outputs, and integrating knowledge graphs into RAG solutions for improved grounding.
• Experience or exposure to advanced GenAI applications in insurance, such as compliance-aware prompt engineering, document generation, objection response automation, synthetic data generation for low-frequency events, and customer sentiment modeling from surveys, call transcripts, or inspection notes.
• Experience working within enterprise AI governance frameworks, aligning conversational AI and analytics solutions with compliance, privacy, documentation, and ethical standards.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
India GCC-Puppalaguda Village
• Foundational knowledge of insurance products, processes (including underwriting, claims, and pricing), and regulatory environments, with demonstrated ability to apply analytics and AI solutions within a regulated industry context. • Experience with advanced NLP and Generative AI capabilities, including embeddings, hybrid and dense retrieval strategies, advanced chunking, prompt engineering, structured outputs, and integrating knowledge graphs into RAG solutions for improved grounding. • Experience or exposure to advanced GenAI applications in insurance, such as compliance-aware prompt engineering, document generation, objection response automation, synthetic data generation for low-frequency events, and customer sentiment modeling from surveys, call transcripts, or inspection notes.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.