Cloud Solution Engineer (Genomics & AI)

The opportunity Oracle is seeking a senior pre-sales engineer with expertise in genomics, software engineering, and applied AI/ML. You will help biotechnology and pharmaceutical companies, research institutions, and genomics laboratories evaluate and adopt Oracle Cloud Infrastructure (OCI) 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 guide customer decisions 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 support customer decisions 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., * 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 support customer decisions 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.

• Eight or more years of relevant technical experience, including hands-on work, in bioinformatics, computational genomics, scientific computing, cloud engineering, or closely related areas.
• 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.
• Experience designing cloud or high-performance computing solutions, including compute and storage sizing, workflow scheduling, security, performance optimization, and cost management.
• Demonstrated executive presence, strong interpersonal skills, and clear verbal and written communication. 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., * 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, 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.

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

Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives.

True innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing a workforce that promotes opportunities for all with competitive benefits that support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs.