Lead AI Engineer

🕒 September 28

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 17%

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Logo of Exavalu

Exavalu

201 - 500 employees

Founded 2018

💼 Consulting

🏥 Healthcare

🛡️ Insurance

Consulting • Healthcare • Insurance

Exavalu is a business advisory and technology consulting firm that partners with enterprises to deliver high-impact digital transformation. Run by former CIOs, CXOs, and consulting principals, Exavalu offers strategic advisory, core systems transformation, systems integration, data & analytics, innovation and privacy/compliance solutions across regulated sectors. The firm focuses on Insurance, Banking & Financial Services, and Healthcare & Life Sciences, providing industry-tailored technology implementations and program leadership using partners like Guidewire, Salesforce, MuleSoft, PegaSystems and AWS.

📋 Description

• Design and implement end-to-end AI/ML solutions, including LLM-based applications • Build RAG pipelines using vector databases and enterprise data sources • Build machine learning models with automated training, validation, monitoring, and retraining • Develop APIs and services to operationalize AI capabilities across the organization • Build ingestion for multimodal content and transformation pipelines for structured and unstructured data • Integrate AI workflows with enterprise systems such as policy, claims, and billing systems • Ensure data quality, traceability, reliability, and governance in AI pipelines • Implement CI/CD for AI/ML workflows • Deploy, monitor, and maintain models in production • Manage model versioning, performance monitoring, and retraining processes • Develop solutions using Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related AWS services • Contribute to the evolving use of AWS Bedrock • Implement LLM guardrails including grounding, validation, and safety • Ensure secure handling of sensitive data such as PII and financial data • Build systems aligned with enterprise governance and compliance standards

🎯 Requirements

• 10+ years in software or data engineering • 5 years of AI/ML engineering experience • Hands-on experience building production AI/ML systems • Experience with RAG pipelines, LLMs, or NLP-based systems • Experience with AWS Bedrock or similar GenAI platforms • Experience with data pipelines and distributed systems • Experience deploying and operating systems in AWS • Working knowledge of MLOps practices, including CI/CD, monitoring, and versioning • Preferred: Experience with vector databases such as Pinecone or Weaviate • Preferred: Experience in regulated industries such as insurance, finance, or healthcare • Preferred: Exposure to microservices and containerized environments such as Docker and Kubernetes

🏖️ Benefits

• Flexible work arrangements, including part-time work, working outside normal 9–5 business hours, or working remotely • Welcome back program supporting people returning to work after a long break due to health or family reasons • Inclusive workplace culture embracing diverse perspectives • Career growth opportunities

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