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Salary
$119k – $194k per year
Location
In office (United States)
Seniority
Staff · 8+ years exp
Visa
H-1B filings in 12 months: 1,038 · for this role: 747 · green card filings: 729

Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Nov 9, 2026. Oracle scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Oracle is an American enterprise technology company founded in 1977 by Larry Ellison, Bob Miner and Ed Oates, and headquartered in Austin, Texas. It built its business on the Oracle Database, still the reference relational engine for large transactional systems, and has expanded into a full applications suite covering finance, human resources, supply chain and customer experience through Fusion Cloud and NetSuite. Its fastest growing segment is Oracle Cloud Infrastructure, which the company has positioned aggressively for AI training and inference workloads through large multi-year capacity contracts.
The opportunity Oracle is seeking a senior pre-sales engineer with expertise in genomics, software engineering, and applied AI/ML. You will help molecular diagnostics companies, genomics platform providers, biotechnology and pharmaceutical companies, research institutions, and genomics laboratories evaluate and adopt Oracle Cloud Infrastructure (OCI) compute, networking, and storage for genomic discovery, precision medicine, and therapeutic research. Partnering with sales, you will translate scientific and business requirements into cloud architectures, demonstrations, and proofs of concept that help win OCI infrastructure business and establish a path to production.What you will do
  • Design and demonstrate genomic analysis workflows, including WGS/WES germline and somatic variant calling, bulk RNA-seq, and single-cell analysis. Apply appropriate quality control, processing, and interpretation methods for each data type.

  • Design computational solutions for functional genomics and genome engineering research, including CRISPR screen analysis, gene regulation, perturbation response, and therapeutic target identification and prioritization. Partner with experimental scientists to connect model predictions with biological validation.

  • Develop and evaluate AI/ML approaches for variant prioritization, multi-omics integration, biomarker discovery, and genotype-phenotype modeling. Assess genomic foundation models and sequence-based deep learning where they address a defined scientific question.

  • Build reproducible pipelines using Python or R, workflow orchestration, containers, version control, and automated testing. Integrate sequencing platforms, laboratory information management systems, sample metadata, and downstream analytical applications.

  • Architect CPU and GPU computing, storage, networking, and data platforms on OCI. Benchmark accelerated genomics and model training or inference against customer baselines for accuracy, throughput, turnaround time, and cost per sample.

  • Establish sound model evaluation with appropriate cohort separation, controls for data leakage and batch effects, subgroup analysis, and uncertainty assessment. Maintain data provenance, pipeline and model versioning, and reproducibility.

  • Lead customer workshops, demonstrations, and proofs of concept with agreed success criteria. Communicate findings, architecture tradeoffs, costs, and recommendations through presentations and written proposals that secure competitive technical wins and support sales closure and production planning.

  • Partner with sales, product, and engineering teams; advise scientific and executive stakeholders; mentor colleagues; and publish reusable architectures, solution code, and technical content. Bring customer requirements into product roadmap discussions.

Required qualifications
  • Eight or more years of relevant technical experience combining hands-on expertise in genomics or molecular biology with cloud or high-performance computing infrastructure engineering.

  • Demonstrated ability to build and troubleshoot genomic analysis workflows, with a strong understanding of sequencing data, genomic variation, statistical analysis, and the biological interpretation of results.

  • Strong programming skills in Python and working proficiency in R or an equivalent scientific computing language. Experience with Linux, Git, containers, and workflow tools such as Nextflow, WDL/Cromwell, or Snakemake.

  • Practical experience developing, evaluating, or deploying machine learning models for biological or other complex scientific datasets, using frameworks such as PyTorch, TensorFlow, or scikit-learn.

  • Hands-on experience designing cloud or high-performance computing solutions for genomic or molecular workloads, including compute, networking, and storage sizing, workflow scheduling, security, performance optimization, and cost management.

  • Demonstrated executive presence, strong interpersonal skills, and excellent verbal and written communication, including in-person presentations to customer executives and compelling executive-level written proposals and recommendations. Able to translate complex scientific and technical requirements into actionable recommendations, build trusted relationships with researchers and senior decision-makers, and connect technical tradeoffs to business priorities, costs, and measurable outcomes.

  • Ability to travel up to 50 percent domestically and internationally.

Preferred qualifications
  • Bachelor’s degree in bioinformatics, computational biology, computer science, genetics, engineering, mathematics, or a related field, or equivalent relevant experience. An advanced degree in a relevant field is highly desirable.

  • Depth in one or more areas: population or translational genomics; oncology and liquid biopsy; rare disease analysis; single-cell or spatial omics; epigenomics and 3D genome biology; or CRISPR and perturbation-based functional genomics.

  • Experience with tools such as GATK, DeepVariant, NVIDIA Parabricks,Illumina DRAGEN, or comparable genomics software; GPU acceleration; distributed computing; and large-scale genomic datasets.

  • Experience adapting genomic or biological foundation models, integrating multimodal biological data, or building evidence-grounded AI assistants for scientific workflows.

  • Familiarity with OCI or another major cloud platform, Kubernetes, infrastructure as code, experiment tracking, and model deployment and monitoring.

  • Experience supporting sensitive genomic data with access controls, encryption, audit trails, consent-aware data use, and customer validation requirements.

  • Customer-facing solution architecture, technical consulting, or presales experience, including proofs of concept and successful transitions to production.

What success looks like

Customers select and adopt OCI compute, networking, and storage based on demonstrated scientific value and a compelling business case. Proofs of concept meet agreed success criteria, demonstrate measurable improvements against customer baselines, and establish a credible path to production. Technical wins translate into closed sales and growing OCI consumption. Reusable solutions accelerate subsequent customer evaluations and adoption.

  • Design and demonstrate genomic analysis workflows, including WGS/WES germline and somatic variant calling, bulk RNA-seq, and single-cell analysis. Apply appropriate quality control, processing, and interpretation methods for each data type.
  • Design computational solutions for functional genomics and genome engineering research, including CRISPR screen analysis, gene regulation, perturbation response, and therapeutic target identification and prioritization. Partner with experimental scientists to connect model predictions with biological validation.
  • Develop and evaluate AI/ML approaches for variant prioritization, multi-omics integration, biomarker discovery, and genotype-phenotype modeling. Assess genomic foundation models and sequence-based deep learning where they address a defined scientific question.
  • Build reproducible pipelines using Python or R, workflow orchestration, containers, version control, and automated testing. Integrate sequencing platforms, laboratory information management systems, sample metadata, and downstream analytical applications.
  • Architect CPU and GPU computing, storage, networking, and data platforms on OCI. Benchmark accelerated genomics and model training or inference against customer baselines for accuracy, throughput, turnaround time, and cost per sample.
  • Establish sound model evaluation with appropriate cohort separation, controls for data leakage and batch effects, subgroup analysis, and uncertainty assessment. Maintain data provenance, pipeline and model versioning, and reproducibility.
  • Lead customer workshops, demonstrations, and proofs of concept with agreed success criteria. Communicate findings, architecture tradeoffs, costs, and recommendations through presentations and written proposals that secure competitive technical wins and support sales closure and production planning.
  • Partner with sales, product, and engineering teams; advise scientific and executive stakeholders; mentor colleagues; and publish reusable architectures, solution code, and technical content. Bring customer requirements into product roadmap discussions.
Disclaimer:

Certain U.S. based or U.S. customer or client-facing roles may be required to comply with applicable requirements, such as immunization/occupational health mandates, and/or drug testing requirements.

Range and benefit information provided in this posting are specific to the stated locations only

US: Hiring Range in USD from: $118,700 to $194,400 per annum. May be eligible for equity. Eligible for commission with an estimated pay mix of 70/30.

Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business.

Candidates are typically placed into the range based on the preceding factors as well as internal peer equity.

Oracle US offers a comprehensive benefits package which includes the following:

1. Medical, dental, and vision insurance, including expert medical opinion

2. Short term disability and long term disability

3. Life insurance and AD&D

4. Supplemental life insurance (Employee/Spouse/Child)

5. Health care and dependent care Flexible Spending Accounts

6. Pre-tax commuter and parking benefits

7. 401(k) Savings and Investment Plan with company match

8. Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.

9. 11 paid holidays

10. Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.

11. Paid parental leave

12. Adoption assistance

13. Employee Stock Purchase Plan

14. Financial planning and group legal

15. Voluntary benefits including auto, homeowner and pet insurance

The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted.

As part of Oracle's onboarding process and consistent with applicable law, US-based employees are required to complete identity verification, which involves the collection and processing of their biometric information. Accommodations to this requirement may be granted following an individualized assessment.

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