rockITdata is a unique SDVOSB services company that partners with leading commercial healthcare/life sciences organizations on cutting edge innovations. They are seeking an AI/ML Engineer responsible for designing, building, and optimizing AI-powered capabilities within an Amazon Connect contact center environment running in AWS GovCloud (IL4).
Responsibilities:
- Configure and optimize Amazon Bedrock Agents for virtual agent fulfillment, real-time coaching, call summarization, and post-call quality analysis
- Design, version-control, and iteratively refine prompt templates for each AI capability, measuring performance against SLA accuracy targets (≥95% QA match)
- Build and maintain the AWS Bedrock Knowledge Base, including content ingestion pipelines synced from Salesforce and semantic retrieval optimization using Amazon Nova models
- Develop coaching rulesets that map required disclosures, HIPAA-sensitive language patterns, and DHA-mandated scripts to specific call types for real-time compliance monitoring
- Implement QA scoring rubrics for the post-call analysis platform, enabling automated evaluation of sentiment, compliance, accuracy, and resolution effectiveness across 100% of calls
- Configure Bedrock Guardrails for PHI/PII redaction, hallucination detection, prompt-injection protection, and content filtering on every inference call
- Evaluate new Amazon Nova model releases (Nova Pro, Nova Lite, Nova Micro) against production benchmarks for accuracy, latency, and cost efficiency, proposing model swaps through change management
- Collaborate with the Integration Engineer to ensure Bedrock inference outputs are properly formatted for delivery to Salesforce (via Lambda and Platform Events) and to Verint
- Monitor model performance using CloudWatch metrics and QuickSight dashboards; identify and remediate model drift at Day 30 and Day 60 re-benchmarking intervals
- Participate in biweekly sprint demos, presenting AI performance data, prompt tuning results, and accuracy metrics to TriWest stakeholders
- Work with TriWest QA reviewers and SMEs to close knowledge gaps identified through post-call analysis feedback loops
- Ensure all AI inference and logging complies with FedRAMP High, DFARS 252.204-7012, HIPAA, and NIST AI RMF requirements
Requirements:
- 3+ years of experience in applied AI/ML engineering, with hands-on work building LLM-based applications (prompt engineering, RAG architectures, agent frameworks)
- Direct experience with Amazon Bedrock, including Agent configuration, Knowledge Base setup, Guardrails, and foundation model invocation
- Proficiency with Amazon Nova model family or equivalent foundation models (e.g., Claude, Titan) in production environments
- Strong Python and/or Node.js skills for Lambda function development and AI pipeline integration
- Experience with retrieval-augmented generation (RAG) patterns, including vector store management, chunking strategies, and semantic search optimization
- Familiarity with AWS serverless services: Lambda, Kinesis, S3, CloudWatch, and IAM within GovCloud environments
- Understanding of healthcare data privacy requirements (HIPAA, PHI/PII handling) and federal compliance frameworks (FedRAMP, NIST 800-53)
- Experience with version-controlled prompt management and A/B testing of prompt variants
- Strong analytical skills for interpreting model performance metrics and translating findings into prompt or architecture improvements
- Bachelor's degree in Computer Science, Data Science, AI/ML, or related field (or equivalent experience)
- Experience with Amazon Connect, Contact Lens, and contact center AI workflows
- Prior work in FedRAMP High or IL4/IL5 environments
- Familiarity with Salesforce integration patterns (Platform Events, Streaming API, REST/SOAP APIs)
- AWS certifications: Machine Learning Specialty, Solutions Architect, or DevOps Professional
- Experience with TRICARE, DHA, or healthcare insurance domain knowledge
- Background in conversational AI design (IVR, chatbots, voice agents)