Bioinformatics Engineer

Inocras Inc•San Diego, CA

1d•$100,000 - $140,000•Onsite

About The Position

We are seeking a Bioinformatics Engineer who combines a strong foundation in computational biology and genomics with hands-on cloud and software engineering skills. In this role, you will analyze large-scale genomic data and help build the cloud-native systems that operationalize it—turning bioinformatics methods, WGS pipelines, and AI proof-of-concepts into production-grade workflows. Working hands-on with genomic data, you will contribute to WGS pipeline development and help integrate and scale advanced AI capabilities—such as cancer foundation models and LLM-driven agents—into genomic analysis and interpretation workflows, along with the data infrastructure and APIs that deliver genomic insights across the organization. The ideal candidate understands biological data deeply, writes clean and maintainable production code, and is excited to apply modern software, cloud, and AI technologies to genomics, working closely with R&D, clinical, and engineering teams across the company.

Requirements

Master's degree or higher in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related field.
Hands-on experience analyzing high-throughput biological data (NGS/WGS/RNA-seq) and working with standard genomic data formats (FASTQ, BAM/CRAM, VCF).
Proficiency in Python (and/or R) and working knowledge of Linux/Unix command-line environments.
Demonstrated ability to write clean, well-structured code and translate research or prototype scripts into production-ready pipelines.
Hands-on experience with cloud environments (AWS preferred), including deploying bioinformatics workloads.
Ability to produce clear technical documentation and communicate effectively across scientific, clinical, and engineering teams.

Nice To Haves

Strong domain expertise in whole-genome sequencing (WGS) data analysis, particularly with cancer WGS datasets.
Experience with bioinformatics workflow languages and pipeline frameworks (e.g., Nextflow, WDL, Snakemake).
Experience developing, fine-tuning, or evaluating large-scale AI models for genomic and clinical data analysis and interpretation.
Hands-on experience developing LLM agents, prompt workflows, and RAG architectures, including benchmarking to minimize hallucinations.
Experience building workflow orchestration and queue-management systems with tools such as Prefect or Airflow.
Experience designing AWS cloud architectures (e.g., ECS, Lambda, S3, ECR) to serve and deploy analytical or AI workloads.
Familiarity with containerization (Docker), CI/CD pipelines, and infrastructure-as-code.

Responsibilities

Analyze large-scale genomic data (WGS, RNA-seq) and contribute to the benchmarking and optimization of Inocras's WGS analysis pipelines.
Design, develop, and validate in-house methods, scripts, and algorithms that advance Inocras's proprietary genomic analysis capabilities.
Deploy AI-driven capabilities—such as cancer foundation models and LLM agents—into genomic interpretation and clinical workflows.
Re-engineer bioinformatics methods, research prototypes, and AI proofs-of-concept into scalable, production-grade workflows on AWS.
Build and maintain scalable genomic data infrastructure and APIs (e.g., REST), using AWS genomics and data services (e.g., HealthOmics, S3, Athena, Glue).
Follow software engineering best practices—version control, testing, containerization (Docker), and documentation—to ensure pipeline reliability and maintainability.