Rishi Sethia

• Designed and maintained distributed scheduling framework executing 10,000+ jobs per month across 20+ EC2 instances with dynamic core reallocation and failure recovery
• Refactored execution pipeline architecture, eliminating hard-coded task flows and introducing modular orchestration layers
• Implemented job monitoring, stuck-process detection, and auto-recovery mechanisms for long-running workloads
• Improved resource utilization under concurrent workloads through intelligent core redistribution

Impact: Increased execution reliability, improved throughput, and reduced manual operational overhead across 30+ in-house systems.

• Re-engineered legacy profiling system reducing runtime from 24+ hours to under 1 hour, enabling same-day processing cycles
• Optimized compute-intensive modeling utility to sub-5-minute execution time through algorithmic restructuring and database-level tuning
• Identified and resolved hierarchy mismatches, data corruption issues, and execution inconsistencies in production environments
• Applied database vacuuming and storage tuning strategies to sustain long-term performance stability

Impact: Delivered order-of-magnitude runtime improvements and improved production stability.

• Managed AWS infrastructure supporting 20+ EC2 instances across dev, staging, and production environments
• Governed infrastructure spanning multiple AWS accounts and environments
• Optimized storage footprint across 50TB of data through archival design and lifecycle policies
• Automated lifecycle management for 200+ cloud resources, reducing manual provisioning and eliminating idle compute
• Reduced AWS infrastructure spend from ~$20K/month to ~$12K/month (~40% reduction) via resource audits, storage compression, and Savings Plan alignment

Impact: Sustained significant cost reduction while maintaining system scalability and availability.

• Developed back end APIs connecting UI layers with computational execution engines
• Resolved high-priority synchronization and execution propagation issues
• Improved logging, error handling, and execution traceability for automation binaries
• Led Gitlab enterprise deployment and migration from legacy version control systems
• Configured branch protection, CI/CD integration, and repository governance
• Built internal automation utility enabling controlled repository creation and access management
• Conducted engineering training on Git workflows and repository management

• Coordinated with other engineers to evaluate and improve software and hardware interfaces.
• Collaborated with management, internal and development partners regarding software application design status and project progress.
• Reviewed project specifications and designed technology solutions that met or exceeded performance expectations.
• Provided direction and guidance to process improvements and established policies.
• Analyzed proposed technical solutions based on customer requirements.
• Worked on development and deployment of DKRON, scheduler application for execution of company pipeline.

• Development of Neo4J database for existing model and working on backend using Flask
• Associated with team on revamp of existing Infrastructure
• Participated in continuous improvement by generating suggestions, engaging in problem-solving activities to support teamwork.
• Resolved problems, improved operations and provided exceptional service.
• Drove operational improvements which resulted in savings and improved profit margins.
• Collaborated with team members to achieve target results.
• Identified issues, analyzed information and provided solutions to problems.

• Resolved problems, improved operations and provided exceptional service.
• Maintained energy and enthusiasm in fast-paced environment.
• Maximized performance by monitoring daily activities and mentoring team members.
• Developed and initiated projects, managed costs, and monitored performance.
• Developed, modified and rectified various NGS tools and pipelines, To name few GWAS, RNAseq, MetaGenomics. VCF Verification Tool.
• Developed Metagenomics Pipeline, which takes in fastq file(s) from user and generates OTUs along with heat-map
• Reviewed project specifications and designed technology solutions that met or exceeded performance expectations
• Technologies Used:- Python, Bash, AWS Cloud, Docker

• Client: MobileIron INC (Now Ivanti)
• Debugged code and located root causes of problems by reviewing configuration files and logs.
• Identified and tracked defects with software and supported developers in resolving problems by completing additional tests.
• Wrote and optimized test cases to maximize success of manual software testing with consistent, thorough approaches.
• Designed and developed automation scripts using open source tools.
• Authored and maintained well-organized, efficient and successful manual test cases for entire team.

• Orchestrator API A command-line interface tool that helps the user to track the Profiles. Key Tasks : Created a terminal based Python API, for end users to track the status of the Profile been processed.
• Next Door Neighbor Using the KNN Approach find the Response of a given Blind Profile. Key Tasks : To develop a tool using the KNN approach to find the given blind profile to be a Responder or
  Non-Responder from the given feature matrix
• Synthetic Patient Creator For a given indication type of cancer, the software would fetch corresponding profiles and its genomics. Based on the gene count and number of profiles, it must create synthetic patients that do not match the initial profile
  Key Tasks: To design the approach to the problem statement, generate the profiles for custom tags which are not present and create the synthetic patient

• MCA (Mutation Component Analysis) Tool An automated tool to induce mutations mimicking a cancer patient’s profile. A drug treatment strategy comprising of a combination of drugs is then predicted using another tool. After this, a combination(s) of drugs which could be a possible treatment to specific profile, is predicted by following tool in pipeline.
• Mutation Profiler Tool which takes gene inputs and traverses through in-house developed mathematical models to fetch aberrations and generate analysis report. This tool was enhanced with new algorithm and rewritten in python, earlier tool took 24+ hours which was brought down to less than hour.
• Integrated Development Environment - IDE
  A browser based Graphical User Interface used to create elements of virtual biological cell, specifying its interaction, dynamics and generate output and update MySQL and SQLite Database Key Tasks : Worked on user login component of project , which included Registration, Login, Forgot
  Password and Reset Password
• Orchestrator Infrastructure independent platform to carry-out end-to-end workflow, from patient processing to carrying out simulation to generation of patient report, all is handled by Orchestrator.
  Key Tasks : Manual Testing of Functionality of Software.
  Monitoring functions to track simulation jobs, in case, a job is stuck, killed or needs to be assigned or auto killed in flow. To handle issues seen in, in-house infrastructure in automated way.