Job Description
Senior Software Engineer - AI-Powered Genomics Platform
Position Overview
We are seeking an exceptional Senior Software Engineer to build the foundational infrastructure for our next-generation AI-powered transcriptome analysis platform. This role combines cutting-edge software engineering with the demands of processing petabyte-scale genomic data and orchestrating complex AI workflows. You will create the robust, scalable systems that enable our LLM and Agentic AI components to transform biological research from traditional pipelines to intelligent, autonomous discovery platforms.
Key Responsibilities
Platform Architecture & Development
- Design and implement distributed systems for processing petabyte-scale genomic datasets
- Build high-performance APIs supporting 10,000+ concurrent AI agent requests
- Develop microservices architecture for modular AI component integration
- Create real-time data streaming pipelines for continuous genomic analysis
- Implement fault-tolerant systems with 99.99% uptime requirements
AI Infrastructure Engineering
Build scalable infrastructure for LLM deployment and inference optimizationDevelop orchestration systems for multi-agent AI workflowsCreate GPU / TPU cluster management for distributed AI processingImplement caching strategies for billion-parameter model inferenceDesign model versioning and A / B testing frameworksData Engineering & Processing
Develop high-throughput pipelines for RNA-seq data processingImplement efficient storage solutions for 20,000+ gene expression matricesCreate data validation and quality control frameworksBuild real-time monitoring for genomic data integrityDesign compression algorithms for efficient genomic data storageIntegration & Interoperability
Create unified APIs connecting LLMs, agents, and biological databasesImplement FHIR-compliant interfaces for clinical data integrationBuild connectors for major genomic databases (GEO, TCGA, GTEx)Develop webhook systems for laboratory instrument integrationCreate SDKs for researcher and clinical user accessRequired Qualifications
Technical Expertise
BS / MS in Computer Science, Software Engineering, or related field5+ years of software engineering experience with Python as primary languageExpert-level proficiency in Python async programming and frameworks (FastAPI, asyncio)Strong experience with distributed systems (Kubernetes, Docker, microservices)Proven track record with high-throughput data processing systemsDeep understanding of database systems (PostgreSQL, MongoDB, Redis)Infrastructure & DevOps
Experience with cloud platforms (AWS, GCP, or Azure) at scaleProficiency with infrastructure as code (Terraform, Pulumi)Strong background in CI / CD pipelines and GitOps practicesExperience with observability tools (Prometheus, Grafana, ELK stack)Knowledge of message queuing systems (Kafka, RabbitMQ, Celery)AI / ML Engineering
Experience deploying and scaling ML models in productionFamiliarity with ML frameworks (PyTorch, TensorFlow) from an engineering perspectiveUnderstanding of GPU programming and optimizationExperience with model serving frameworks (TorchServe, TensorFlow Serving, Ray Serve)Preferred Qualifications
Experience with bioinformatics tools and pipelinesKnowledge of genomic data formats (FASTQ, BAM, VCF)Familiarity with scientific computing (NumPy, SciPy, Pandas)Understanding of HIPAA compliance and healthcare data securityExperience with real-time systems and streaming architecturesBackground in building developer platforms and APIsContributions to open-source projectsKey Performance Metrics
AchieveSupport 1M+ daily genomic analyses with linear scalingMaintain 99.99% platform uptime with zero data lossReduce infrastructure costs by 40% through optimizationEnable 5x faster genomic pipeline executionSuccessfully integrate 10+ external biological databasesIntegration Responsibilities
Team Collaboration
Partner with LLM Engineers to optimize model serving infrastructureSupport Agentic AI Engineers with scalable agent execution platformsCollaborate with Bioinformaticians on pipeline optimizationWork with Security teams on HIPAA-compliant implementationsPlatform Leadership
Define engineering standards and best practicesMentor junior engineers on distributed systems designLead architecture reviews and technical decision-makingDrive adoption of new technologies and methodologiesTechnical Stack
Core Technologies
Languages : Python (primary), Go, Rust (performance-critical components)Frameworks : FastAPI, Celery, Ray, DaskDatabases : PostgreSQL, MongoDB, Redis, InfluxDBInfrastructure : Kubernetes, Docker, Terraform, ArgoCDMonitoring : Prometheus, Grafana, OpenTelemetryML / AI : PyTorch, Ray Serve, MLflow, Weights & BiasesDomain-Specific Tools
Genomics : Nextflow, Snakemake, CWLData Formats : Apache Parquet, HDF5, ZarrCompute : SLURM, AWS Batch, Google Cloud Life SciencesWhat We Offer
Build infrastructure powering the future of precision medicineWork with cutting-edge AI and genomics technologiesCollaborate with world-class engineers and scientistsCompetitive salary ($170,000 - $260,000) based on experienceComprehensive benefits with equity participation$5,000 annual learning and development budgetTop-tier hardware and development environmentFlexible remote work with quarterly team offsitesThe Engineering Challenge
This role offers unique engineering challenges at the intersection of :
Scale : Processing petabytes of genomic data dailyPerformance : Sub-second response times for complex biological queriesReliability : Clinical-grade system reliabilityInnovation : Enabling autonomous AI agents in biological discoveryApplication Requirements
Please submit :
Resume / CV highlighting relevant infrastructure projectsGitHub profile or code samples demonstrating Python expertiseSystem design document or architecture diagram from a past projectBrief description of the most challenging scaling problem you've solvedOptional : Open-source contributions or technical blog postsContact : careers@ayassbioscience.com