Senior AI Engineer

Milestone Technologies; Ernakulam; On-site; INR 1,500,000 - 2,400,000; Full time

Job summary

Milestone-Technologie in India seeks a Senior AI Engineer to lead the technical build of AI solutions for healthcare/claims domain. You will design pipelines for unstructured data, build extraction and classification models, and ensure scalable, auditable AI systems.

The role requires 6-10 years in software/ML, with 2+ years in Gen AI and document parsing. You will mentor engineers, collaborate with business stakeholders, and implement robust data governance and compliance in production.

Qualifications

• Strong Python and software fundamentals including APIs, testing, Git, CI/CD.
• Hands-on experience with LLM APIs and multimodal models for extraction and classification.
• Experience with document AI and OCR services and handling low-quality scans.
• Experience building email ingestion pipelines with attachment parsing.
• Understanding of confidence scoring, calibration, and precision/recall trade-offs for automation decisions.
• Production deployment on cloud with scalable queue-based/event-driven architectures.
• Ability to explain design choices and risks to business users.

Responsibilities

• Design pipelines that process unstructured data.
• Build extraction logic to find key terms and metadata.
• Build multimodal classification (text and image).
• Design the system to scale during catastrophe events.
• Build extraction and validation rules.
• Classify routine operational requests (insurance evidence, cancellations, payments, documents).
• Implement rule-driven automation for known, low-risk scenarios.
• Define and tune confidence thresholds for auto-fill, auto-classification, auto-routing, and manual review.

Skills

Python

APIs

Testing

Git

CI/CD

LLM APIs

Multimodal models

OCR/Document AI

Cloud deployment

Communication

Education

Degree in CS/IT/Data Science

Job description

We're looking for a Senior AI Engineer to lead the technical build of AI-solutions

Experience: 6-10 Years in Software/ML Engineering, including 2+ years in Gen AI and Document Parsing.

Key Responsibilities

• Design pipelines that process unstructured data.
• Build extraction logic to find key terms and metadata.
• Build multimodal classification (text and image)
• Design the system to scale during catastrophe events
• Build extraction and validation rules.
• Classify routine operational requests such as evidence of insurance, cancellations, payment plan changes, document uploads, and inspection reports.
• Implement rule-driven automation for known, low-risk scenarios.
• Define and tune confidence thresholds for auto-fill, auto-classification, auto-routing, and manual review, including handling for multiple-match results.
• Design human-in-the-loop review, user override, audit logging, and traceability for every AI-suggested or AI-executed action.
• Integrate with shared email inboxes, workflow queues, and other channels.
• Build evaluation sets.
• Protect PII and sensitive claim data through access controls, retention rules, and compliance requirements.
• Work with business architects and client stakeholders.
• Review code and designs, set engineering standards, and mentor AI engineers.

Required Skills

• Strong Python and software engineering fundamentals: APIs, testing, Git, CI/CD.
• Hands-on experience with LLM APIs, including multimodal (vision) models, for extraction and classification.
• Experience with document AI and OCR services and handling low-quality scans.
• Experience building email ingestion pipelines with attachment parsing.
• Solid understanding of confidence scoring, calibration, and precision/recall trade-offs for automation decisions.
• Production deployment on cloud, with queue-based and event-driven architectures that scale under load.
• Ability to explain design choices and risks clearly to claims and underwriting business users.

Nice to Have

• Experience with entity matching with system of records data (Fuzzy matching, identifier validation)
• Fine Tuning or small model optimization for classification at high volume.
• Interest in or exposure to the insurance or financial services domain.
• Cloud AI Certification.
• Degree in Computer Science, IT, Data Science, or a related field.