Senior Software Developer – Neurotech & AI Platform Location: Remote (USA)

About the Role We are seeking a Senior Software Developer to build a scalable, AI-driven cloud backend for QEEG analysis and neurofeedback. You will architect AWS serverless systems that process real-time EEG data and deliver personalized digital therapeutics through ML inference and LLM-powered recommendations. Key Responsibilities Design HIPAA-compliant serverless microservices (.NET 8 C#, AWS Lambda, API Gateway) to ingest and process real-time EEG streams from BrainBit wearable devices Build real-time EEG signal processing pipelines on Kinesis Data Streams — artifact removal, bandpass filtering, and spectral analysis across all clinically relevant bands Deploy and serve ONNX-format ML models via Amazon SageMaker for real-time biomarker inference (focus, relaxation, stress states) Integrate Amazon Bedrock (LLM) to generate personalized neurofeedback protocol recommendations from session data Implement WebSocket-based closed-loop feedback (API Gateway + Lambda) to deliver real-time brain state events to mobile clients Ensure GDPR/HIPAA compliance: PHI encryption, KMS key management, CloudTrail audit logging, and AWS BAA-covered services Own infrastructure as code using AWS CDK (C#) or SAM; maintain CI/CD via GitHub Actions Required Skills .NET C# (8+), AWS Lambda, API Gateway, Kinesis, DynamoDB, S3 QEEG and neurofeedback domain knowledge is required. Candidates must be familiar with: EEG frequency bands: Delta (0.5–4 Hz), Theta (4–8 Hz), Alpha (8–12 Hz), SMR (12–15 Hz), Beta (15–30 Hz), High Beta (30–40 Hz), Gamma (40+ Hz) Standard neurofeedback protocols: SMR Up-Training, Alpha/Theta, Beta Up-Training, Theta Down-Training, Asymmetry training (e.g. Alpha asymmetry F3/F4) Electrode placement systems: 10-20 International System; sites including Cz, Fz, Pz, F3, F4, T3, T4, O1, O2 Artifact types and removal: eye blink (EOG), muscle noise (EMG), 50/60 Hz line noise Band power ratios used clinically: Theta/Beta ratio, Alpha peak frequency, coherence metrics QEEG normative database comparison (e.g. NeuroGuide, HBImed) Signal processing: FFT, bandpass filtering, Butterworth/IIR filters, ICA — ideally in C# (Math.NET Numerics or equivalent) ML model deployment: ONNX Runtime, Amazon SageMaker real-time endpoints LLM integration: Amazon Bedrock or equivalent managed LLM APIs Real-time streaming architecture (Kinesis, WebSockets) HIPAA/GDPR compliance in AWS environments Preferred (8+ years experience) Building a 0→1 neurofeedback, biofeedback, or digital therapeutics platform HRV analytics and multi-modal biosignal fusion (EEG + HRV) Experience with clinical neurofeedback workflows and protocol design Familiarity with BLE device integration on mobile (Flutter or React Native) Knowledge of Z-score neurofeedback and live sLORETA surface training