Senior Software Engineer - AI-Powered Genomics Platform

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 optimization Develop orchestration systems for multi-agent AI workflows Create GPU/TPU cluster management for distributed AI processing Implement caching strategies for billion-parameter model inference Design model versioning and A/B testing frameworks Data Engineering & Processing Develop high-throughput pipelines for RNA-seq data processing Implement efficient storage solutions for 20,000+ gene expression matrices Create data validation and quality control frameworks Build real-time monitoring for genomic data integrity Design compression algorithms for efficient genomic data storage Integration & Interoperability Create unified APIs connecting LLMs, agents, and biological databases Implement FHIR-compliant interfaces for clinical data integration Build connectors for major genomic databases (GEO, TCGA, GTEx) Develop webhook systems for laboratory instrument integration Create SDKs for researcher and clinical user access Required Qualifications Technical Expertise BS/MS in Computer Science, Software Engineering, or related field 5+ years of software engineering experience with Python as primary language Expert-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 systems Deep understanding of database systems (PostgreSQL, MongoDB, Redis) Infrastructure & DevOps Experience with cloud platforms (AWS, GCP, or Azure) at scale Proficiency with infrastructure as code (Terraform, Pulumi) Strong background in CI/CD pipelines and GitOps practices Experience 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 production Familiarity with ML frameworks (PyTorch, TensorFlow) from an engineering perspective Understanding of GPU programming and optimization Experience with model serving frameworks (TorchServe, TensorFlow Serving, Ray Serve) Preferred Qualifications Experience with bioinformatics tools and pipelines Knowledge of genomic data formats (FASTQ, BAM, VCF) Familiarity with scientific computing (NumPy, SciPy, Pandas) Understanding of HIPAA compliance and healthcare data security Experience with real-time systems and streaming architectures Background in building developer platforms and APIs Contributions to open-source projects Key Performance Metrics Achieve

Support 1M+ daily genomic analyses with linear scaling Maintain 99.99% platform uptime with zero data loss Reduce infrastructure costs by 40% through optimization Enable 5x faster genomic pipeline execution Successfully integrate 10+ external biological databases Integration Responsibilities Team Collaboration Partner with LLM Engineers to optimize model serving infrastructure Support Agentic AI Engineers with scalable agent execution platforms Collaborate with Bioinformaticians on pipeline optimization Work with Security teams on HIPAA-compliant implementations Platform Leadership Define engineering standards and best practices Mentor junior engineers on distributed systems design Lead architecture reviews and technical decision-making Drive adoption of new technologies and methodologies Technical Stack Core Technologies Languages: Python (primary), Go, Rust (performance-critical components) Frameworks: FastAPI, Celery, Ray, Dask Databases: PostgreSQL, MongoDB, Redis, InfluxDB Infrastructure: Kubernetes, Docker, Terraform, ArgoCD Monitoring: Prometheus, Grafana, OpenTelemetry ML/AI: PyTorch, Ray Serve, MLflow, Weights & Biases Domain-Specific Tools Genomics: Nextflow, Snakemake, CWL Data Formats: Apache Parquet, HDF5, Zarr Compute: SLURM, AWS Batch, Google Cloud Life Sciences What We Offer Build infrastructure powering the future of precision medicine Work with cutting-edge AI and genomics technologies Collaborate with world-class engineers and scientists Comprehensive benefits with equity participation $5,000 annual learning and development budget Top-tier hardware and development environment Flexible remote work with quarterly team offsites The Engineering Challenge This role offers unique engineering challenges at the intersection of: Scale: Processing petabytes of genomic data daily Performance: Sub-second response times for complex biological queries Reliability: Clinical-grade system reliability Innovation: Enabling autonomous AI agents in biological discovery