Ayass BioScience LLC
Senior Software Engineer - AI-Powered Genomics Platform - Biotech Industry
Ayass BioScience LLC, Frisco, Texas, United States, 75034
Senior Software Engineer - AI-Powered Genomics Platform - Biotech Industry
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 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 Build scalable infrastructure for LLM deployment and inference optimization Develop orchestration systems for multi-agent AI workflows Implement caching strategies for billion-parameter model inference Design model versioning and A/B testing frameworks 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 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) 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 Successfully integrate 10+ external biological databases
Integration Responsibilities
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 Define engineering standards and best practices 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) ML/AI:
PyTorch, Ray Serve, MLflow, Weights & Biases
Domain-Specific Tools Genomics:
Nextflow, Snakemake, CWL
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 Competitive salary ($170,000 - $260,000) based on experience 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 Innovation:
Enabling autonomous AI agents in biological discovery
Application Requirements
Please submit: Resume/CV highlighting relevant infrastructure projects System design document or architecture diagram from a past project Brief description of the most challenging scaling problem you've solved Optional: Open-source contributions or technical blog posts
Contact:
careers@ayassbioscience.com #J-18808-Ljbffr
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 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 Build scalable infrastructure for LLM deployment and inference optimization Develop orchestration systems for multi-agent AI workflows Implement caching strategies for billion-parameter model inference Design model versioning and A/B testing frameworks 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 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) 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 Successfully integrate 10+ external biological databases
Integration Responsibilities
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 Define engineering standards and best practices 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) ML/AI:
PyTorch, Ray Serve, MLflow, Weights & Biases
Domain-Specific Tools Genomics:
Nextflow, Snakemake, CWL
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 Competitive salary ($170,000 - $260,000) based on experience 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 Innovation:
Enabling autonomous AI agents in biological discovery
Application Requirements
Please submit: Resume/CV highlighting relevant infrastructure projects System design document or architecture diagram from a past project Brief description of the most challenging scaling problem you've solved Optional: Open-source contributions or technical blog posts
Contact:
careers@ayassbioscience.com #J-18808-Ljbffr