• Implemented a backend service that allows users to upload mobile application binaries for testing, including S3 storage integration and metadata persistence (user, organization, timestamps, and asset details) in DynamoDB.

• Built a retrieval service that returns all uploaded application assets and associated metadata for a given organization, enabling smooth selection and reuse in automated testing workflows.

• Developed a status retrieval service that exposes real-time installation progress to the frontend by querying DynamoDB and returning structured JSON responses.

• Built lifecycle management APIs to start and stop AI-driven testing agents for a given execution run, ensuring controlled orchestration of test sessions.

• Developed a background worker service to track mobile app installation status on AWS Device Farm, aggregating event updates and persisting status records in DynamoDB.

• Optimized the Docker CI build pipeline by restructuring build stages and caching dependencies, reducing build times by 60% and build context size by 97.5%, significantly improving CI/CD throughput and developer productivity.

• Built an LLM-agnostic agent layer enabling seamless dynamic switching between OpenAI, Groq and Gemini through environment variables, ensuring zero downtime and uninterrupted operations.

• Built an end-to-end Typeahead Search System that improved recruiter workflow by surfacing personalized suggestions based on search history, frequency, and recency.

• Designed a new MongoDB collection and schema to store user-specific search history, including query text, truncated display text, hard filters, timestamps, and usage statistics.

• Implemented intelligent deduplication logic to detect near-duplicate queries, merge history, update use-count, refresh timestamps, and maintain a rolling limit of the most recent 50 queries.

• Developed a Redis-powered caching layer (1-hour TTL) for fast prefix matching, achieving sub-100ms response times with graceful fallback to MongoDB on cache misses.

• Built a robust Typeahead API with Firebase JWT authentication, cache-first retrieval, ranking logic, and filter-aware suggestion handling.

• Integrated query saving into the search lifecycle: automatically persisted queries, filters, timestamps, and usage stats after each search execution.

• Containerized and monitored the system using Docker, AWS, and DataDog, and produced detailed sequence diagrams and architectural documentation.

• Built and deployed end-to-end automation workflows on Tennr’s healthcare automation platform, using RaeLM (Tennr’s medical-document LLM) to process referrals, eligibility documents, and insurance information with 97% extraction accuracy.

• Designed workflow logic for document classification, data extraction, patient qualification, and insurance verification, ensuring accurate routing and reliable population of client EHR and billing systems.

• Engineered workflow optimizations that reduced approval and processing delays by 20% by improving triage rules, error-handling branches, and follow-up logic for missing or incomplete documents.

• Monitored live automation pipelines across multiple healthcare clients and resolved workflow-level issues, configuration bugs, and edge-case failures, maintaining 100% uptime for all assigned accounts.

• Collaborated with operations and engineering teams to validate outputs, refine extraction rules, and improve system reliability, ensuring consistent performance for clinics, DMEs, and specialty practices.

• Delivered client-specific implementations for Neb Medicals, Aveanna, Gammie, Lymphacare, and other healthcare providers, tailoring automation logic to their documentation formats, reimbursement workflows, and operational needs.

• Worked on backend components for a real-time intelligence and situational-awareness platform that unified data from multi-modal sources such as satellite feeds, structured files, documents, images, and API-based inputs.

• Contributed to the design of ingestion pipelines for processing diverse data formats (JSON, XML, HTML, CSV, PDF, text, images, videos), ensuring smooth normalization and storage across PostgreSQL, MongoDB, and a vector database.

• Implemented backend endpoints in FastAPI to support chat-based querying, document retrieval, and geospatial insight services used across operational teams.

• Assisted with integration of backend services into a Docker-based deployment setup and helped maintain reliable communication between ingestion, storage, and search subsystems.

• Collaborated with senior engineers to refine backend logic, troubleshoot pipeline issues, and strengthen the platform’s ability to handle continuous multi-source data updates.