Lead AI Engineer

Job_Description":"

This is a remote position.

****Build AI Systems (Core Responsibility)

• 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 that automate their training, validation, monitoring, and retraining

• Develop APIs and services to operationalize AI capabilities across the organization

  **Develop Data + AI Pipelines

  • Build ingestion for multimodal content and transformation pipelines for structured and unstructured data

  • Integrate AI workflows with enterprise systems (policy, claims, billing, etc.)

  • Ensure data quality, traceability, reliability, and governance in all AI pipelines

    **Operationalize Models (MLOps)

    • Implement CI/CD for AI/ML workflows

    • Deploy, monitor, and maintain models in production

    • Manage model versioning, performance monitoring, and retraining processes

      **Build on AWS

      • Develop solutions using: Amazon SageMaker, AWS Lambda, S3, Glue, EKS, and related services

      • Contribute to evolving use of AWS Bedrock

        **Apply Responsible AI Practices

        • Implement guardrails for LLM-based systems (grounding, validation, safety)

        • Ensure secure handling of sensitive data (PII, financial, etc.)

        • Build systems aligned with enterprise governance and compliance standards

          **Qualifications:

          **Required

          • 10+ years in software, data engineering, 5 years AI/ML engineering

          • 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 (CI/CD, monitoring, versioning)

            **Preferred

            • Experience with vector databases (Pinecone, Weaviate, etc.)

            • Experience in regulated industries (insurance, finance, healthcare)

            • Exposure to microservices and containerized environments (Docker, Kubernetes)

              Requirements

              **Qualifications:

              **Required

              • 10+ years in software, data engineering, 5 years AI/ML engineering

              • 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 (CI/CD, monitoring, versioning)

                **Preferred

                • Experience with vector databases (Pinecone, Weaviate, etc.)

                • Experience in regulated industries (insurance, finance, healthcare)

                • Exposure to microservices and containerized environments (Docker, Kubernetes)

                  Benefits

                  Diversity Inclusion:

                  Exavalu also promotes flexibility depending on the needs of employees, customers and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely. We also have a welcome back program to help people get back to the mainstream after a long break due to health or family reasons.************************

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