Bioinformatics Engineer

Inocras Inc•San Diego, CA

22h•$100,000 - $140,000•Onsite

About The Position

Inocras is seeking a Bioinformatics Engineer with a foundation in computational biology and genomics and hands-on cloud and software engineering skills. The role analyzes large-scale genomic data and builds cloud-native systems to operationalize bioinformatics methods, WGS pipelines, and AI proofs-of-concept into production-grade workflows. The engineer will work with genomic data, contribute to WGS pipeline development, and help integrate and scale AI capabilities—including cancer foundation models and LLM-driven agents—into genomic analysis and interpretation workflows. The role also supports the data infrastructure and APIs that deliver genomic insights across the organization, working with R&D, clinical, and engineering teams. Inocras is a precision medicine whole-genome platform company focused on accelerating the use of WGS for accurate diagnosis and personalized treatment for cancer and rare diseases. Its proprietary CancerVision platform combines an automated WGS pipeline with bioinformatics and AI-powered digital solutions to generate medical insights for clinical use. This is an onsite, full-time position in San Diego, California, reporting to the Chief Informatics Officer. The listed annual compensation is $100,000–$140,000, based on experience.

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, including NGS, WGS, or RNA-seq, and working with standard genomic data formats such as FASTQ, BAM/CRAM, and VCF.
Proficiency in Python and/or R.
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, preferably AWS, including deploying bioinformatics workloads.
Ability to produce clear technical documentation and communicate effectively across scientific, clinical, and engineering teams.

Nice To Haves

Strong expertise in WGS data analysis, particularly cancer WGS datasets.
Experience with bioinformatics workflow languages and pipeline frameworks such as Nextflow, WDL, or 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, such as ECS, Lambda, S3, and ECR, to serve and deploy analytical or AI workloads.
Familiarity with Docker, CI/CD pipelines, and infrastructure-as-code.

Responsibilities

Analyze large-scale genomic data, including WGS and RNA-seq, and contribute to benchmarking and optimizing Inocras's WGS analysis pipelines.
Design, develop, and validate in-house methods, scripts, and algorithms to advance 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, including REST APIs, using AWS genomics and data services such as HealthOmics, S3, Athena, and Glue.
Apply software engineering best practices, including version control, testing, containerization, and documentation, to support pipeline reliability and maintainability.