Senior AI Engineer - Remote

Overview

Senior AI Engineer - Remote Opportunity at The Mutual Group (TMG), Guide One Insurance, and future members. Design, build, and deploy solutions that leverage large language models (LLMs), Generative AI, and natural language processing (NLP) to enhance customer and agent experiences. This includes developing intelligent automation, AI-powered services, and supporting teams in the responsible and effective use of AI technologies.

• Multimodal Data Processing and Automation:
  Ingest and preprocess diverse file types (PDFs, scanned images, emails, audio, video, structured/unstructured text); apply OCR and speech-to-text to extract meaningful data; use Lang Chain + Lang Graph to orchestrate agentic workflows for parsing and reasoning across multimodal inputs; build AI pipelines to classify, extract, and validate key entities (e.g., policy numbers, claim dates, insured parties); integrate LLMs via Bedrock or Hugging Face to summarize, interpret, and flag anomalies in claims and underwriting documents;
  
  implement retrieval-augmented generation (RAG) using Vector DBs to ground LLM responses in enterprise knowledge.
• AWS Cloud Engineering Activities
• Model Development & Deployment:
  Train and fine-tune models in Sage Maker using custom datasets and embeddings; deploy models as Sage Maker endpoints or Lambda functions for real-time inference; use Step Functions to orchestrate complex AI workflows across services.
• MLOps & Dev Ops Integration:
  Build CI/CD pipelines using tools like Code Pipeline, Git Hub Actions, or Jenkins to automate model training, testing, and deployment; monitor model drift, performance, and compliance using Sage Maker Model Monitor and custom logging; apply Infrastructure as Code (IaC) with Terraform or Cloud Formation for reproducible environments.
• Data Engineering & Pipelines:
  Design scalable ETL pipelines to transform raw multimodal data into structured formats using AWS Glue, Lambda, and Step Functions; store embeddings and metadata in Vector DBs like Pinecone, Weaviate, or Amazon Kendra; ensure data lineage, versioning, and governance using tools like AWS Lake Formation or Apache Atlas.
• Ethical, Legal & Compliance:
  Implement Responsible AI practices (bias detection, explainability, audit trails); ensure HIPAA and SOC2 compliance in data handling and model outputs; use Bedrock Guardrails or custom filters to prevent hallucinations and ensure safe LLM responses.
• Staying Ahead of AI Trends:
  Continuously evaluate new models from Hugging Face, OpenAI, and Anthropic for relevance to insurance workflows; attend AWS AI/ML webinars, contribute to open-source Lang Chain agents, and experiment with agentic architectures; prototype with new AWS services like Amazon Q, Titan models, or multimodal Bedrock endpoints.
• Skills/Requirements:
  Qualifications include a Bachelor’s degree or equivalent experience; 8+ years in software, data, or AI engineering with 3+ years working directly with AI/ML models; experience building and deploying LLMs/GenAI; proficient in Python and ML libraries (Tensor Flow, PyTorch, scikit-learn); experience with Hugging Face, OpenAI APIs, AWS Bedrock, Lang Chain; cloud experience with AWS, Azure, or GCP; data engineering tools (Apache Spark, Kafka, Airflow);
  
  modern data stack (Snowflake, Redshift, Delta Lake, S3, Azure Data Lake, Big Query);
  Dev Ops practices (CI/CD, Docker, Kubernetes); ability to align AI with business needs; prior experience in insurance or regulated industries is a plus.

• $120,000 - $160,000 commensurate with experience, plus bonus eligibility

• Competitive base salary plus incentive plans for eligible team members
• 401(K) retirement plan with company match up to 6%
• Basic life and AD&D, long-term and short-term disability insurance
• Medical, dental and vision plans
• Wellness incentives
• Generous time off (personal, holiday, volunteer)
• Flexible work schedules and hybrid/remote options for eligible positions
• Educational assistance