AI Solutions Engineer

Aditi Consulting; Bothell (WA); Presencial; USD 69 000 - 75 000; Tempo integral

Resumo da oferta

Aditi Consulting is seeking an AI Solutions Engineer in Bothell, WA, to design, build, test, and maintain scalable AI-enabled software, data pipelines, and automation. You will translate stakeholder requirements into reliable data products, dashboards, and governance-compliant workflows for Translational Medicine.

You will collaborate with data scientists, product owners, and enterprise teams to move solutions from requirements to deployment, focusing on reproducibility, security, documentation,

Qualificações

• Proficiency in Python for application development, automation, data processing, API integration, and testing.
• Proficiency in R, including package development or maintenance, ETL workflows, testing, and documentation.
• Strong command of Git and GitHub, including branching and pull requests as well as release and version management.
• Experience with REST APIs and MCP.
• Familiarity with SQL, relational DBs, and other data structures.
• Experience with AWS and/or Databricks.
• Experience with Docker, CI/CD pipelines, and deployment automation.
• Familiarity with Airflow, Nextflow, Snakemake, CWL, or other workflow platforms.

Responsabilidades

• AI Application and Software Engineering: Design, develop, test, document, and maintain AI-enabled applications, dashboards, APIs, and/or workflow-automation solutions using approved models and platforms.
• Data Engineering and Automated Quality Control: Develop and maintain data-ingestion, transformation, reconciliation, validation, and quality-control workflows for clinical biomarker data.
• Software Quality and Reproducibility: Write maintainable, modular, tested, and appropriately documented code.
• Responsible AI and Governance: Design solutions in accordance with applicable responsible AI, privacy, cybersecurity, data-rights, third-party, quality, and regulatory requirements.

Conhecimentos

Python

R

Git & GitHub

REST APIs

SQL

Docker

AWS / Databricks

Airflow

Nextflow

Snakemake

CWL

Linux

Clinical data knowledge

Ferramentas

Docker

Databricks

Copilot Studio

Kubernetes

GitHub

Descrição da oferta de emprego

Payrate: $50.00 - $54.43/hr. Summary: The AI Solutions Engineer will design, build, test, and maintain reusable software, data pipelines, automation, and AI-enabled applications for Translational Medicine. The successful candidate will translate requirements from business, scientific, and operational stakeholders into reliable data products, automated quality-control workflows, dashboards, and agentic AI applications. The engineer will work closely with data scientists, product owners, and enterprise technology teams to move prioritized solutions from requirements through deployment and maintenance. The role is focused on developing scalable technical products, not conducting primary data analysis or building isolated, study-specific tools. Solutions must be secure, well documented, version-controlled, reproducible, and aligned with enterprise and industry data, privacy, cybersecurity, quality, and responsible AI requirements. Responsibilities

• AI Application and Software Engineering: Design, develop, test, document, and maintain AI-enabled applications, dashboards, APIs, and/or workflow-automation solutions using approved models and platforms. Develop modular components that can be reused across programs, studies, disease areas, and workflow types. Create user-friendly applications that make governed data and computational capabilities accessible to scientific and operational users. Evaluate prototypes for feasibility, reliability, scalability, maintainability, and readiness for broader deployment. Implement human review, source visibility, feedback mechanisms, access controls, and appropriate transparency measures for AI-enabled products.
• Data Engineering and Automated Quality Control: Develop and maintain data-ingestion, transformation, reconciliation, validation, and quality-control workflows for clinical biomarker data. Maintain and expand existing R-based software, ETL scripts, and automated QC capabilities. Translate data-transfer specifications, scientific requirements, and business rules into executable code. Develop configurable workflows that reduce repetitive setup and manual intervention across datasets and studies. Produce clear reports, processing logs, QC outputs, and traceable records for scientific and operational review. Preserve source values, surface unresolved exceptions, and ensure workflows fail safely.
• Software Quality and Reproducibility: Write maintainable, modular, tested, and appropriately documented code. Use approved source-control, branching, release, and versioning practices with Git. Maintain traceability among requirements, source data, code versions, tests, outputs, and releases. Contribute to monitoring, logging, error handling, and operational support documentation. Support risk-appropriate peer review and independent code validation.
• Responsible AI and Governance: Design solutions in accordance with applicable responsible AI, privacy, cybersecurity, data-rights, third-party, quality, and regulatory requirements. Document solution architecture, data sources, data flows, intended users, intended use, limitations, and human-oversight mechanisms. Support required AI risk triage, mitigation documentation, and technical reviews. Implement and test agreed technical controls. Escalate governance, privacy, security, data-rights, validation, or regulatory questions to the accountable experts.

Payrate: $50.00 - $54.43/hr. Summary: The AI Solutions Engineer will design, build, test, and maintain reusable software, data pipelines, automation, and AI-enabled applications for Translational Medicine. The successful candidate will translate requirements from business, scientific, and operational stakeholders into reliable data products, automated quality-control workflows, dashboards, and agentic AI applications. The engineer will work closely with data scientists, product owners, and enterprise technology teams to move prioritized solutions from requirements through deployment and maintenance. The role is focused on developing scalable technical products, not conducting primary data analysis or building isolated, study-specific tools. Solutions must be secure, well documented, version-controlled, reproducible, and aligned with enterprise and industry data, privacy, cybersecurity, quality, and responsible AI requirements. Responsibilities

• AI Application and Software Engineering: Design, develop, test, document, and maintain AI-enabled applications, dashboards, APIs, and/or workflow-automation solutions using approved models and platforms. Develop modular components that can be reused across programs, studies, disease areas, and workflow types. Create user-friendly applications that make governed data and computational capabilities accessible to scientific and operational users. Evaluate prototypes for feasibility, reliability, scalability, maintainability, and readiness for broader deployment. Implement human review, source visibility, feedback mechanisms, access controls, and appropriate transparency measures for AI-enabled products.
• Data Engineering and Automated Quality Control: Develop and maintain data-ingestion, transformation, reconciliation, validation, and quality-control workflows for clinical biomarker data. Maintain and expand existing R-based software, ETL scripts, and automated QC capabilities. Translate data-transfer specifications, scientific requirements, and business rules into executable code. Develop configurable workflows that reduce repetitive setup and manual intervention across datasets and studies. Produce clear reports, processing logs, QC outputs, and traceable records for scientific and operational review. Preserve source values, surface unresolved exceptions, and ensure workflows fail safely.
• Software Quality and Reproducibility: Write maintainable, modular, tested, and appropriately documented code. Use approved source-control, branching, release, and versioning practices with Git. Maintain traceability among requirements, source data, code versions, tests, outputs, and releases. Contribute to monitoring, logging, error handling, and operational support documentation. Support risk-appropriate peer review and independent code validation.
• Responsible AI and Governance: Design solutions in accordance with applicable responsible AI, privacy, cybersecurity, data-rights, third-party, quality, and regulatory requirements. Document solution architecture, data sources, data flows, intended users, intended use, limitations, and human-oversight mechanisms. Support required AI risk triage, mitigation documentation, and technical reviews. Implement and test agreed technical controls. Escalate governance, privacy, security, data-rights, validation, or regulatory questions to the accountable experts.

Qualifications

• Bachelor's or master's degree in computer science, software engineering, data science, bioinformatics, computational biology, biomedical engineering, or a related quantitative field.
• At least two years of professional experience developing data-intensive software, scientific applications, data pipelines, AI-enabled applications, or automation solutions in a production setting.
• Demonstrated experience delivering software beyond exploratory notebooks or one-time analyses.
• Experience translating stakeholder needs into technical requirements.
• Experience testing, documenting, releasing, maintaining, and troubleshooting software.
• Experience in life sciences, pharmaceuticals, biotechnology, clinical research, or other regulated environments.

Skills

• Proficiency in Python for application development, automation, data processing, API integration, and testing.
• Proficiency in R, including package development or maintenance, ETL workflows, testing, and documentation.
• Strong command of Git and GitHub, including branching and pull requests as well as release and version management.
• Experience with code documentation, automated testing, logging, debugging, and error handling.
• Experience developing ETL, data-validation, reconciliation, or workflow-automation solutions.
• Working knowledge of Linux development environments.
• Ability to communicate technical concepts to scientific and operational stakeholders.
• Experience with clinical, multi-omics, imaging, pathology, or real-world datasets.
• Experience building generative-AI or agentic applications, structured outputs, evaluation frameworks, or human-in-the-loop approaches.
• Experience with Microsoft Copilot Studio.
• Experience with AWS and/or Databricks.
• Experience with Docker, CI/CD pipelines, and deployment automation.
• Familiarity with SQL, relational DBs, and other data structures.
• Experience with REST APIs and MCP.
• Familiarity with Airflow, Nextflow, Snakemake, CWL, or other workflow platforms.
• Understanding of data provenance, privacy, consent, regulated data, GxP considerations, and risk-based software validation.

Pay Transparency: The typical base pay for this role across the U.S. is:$50.00 - $54.43/hour. Non-exempt positions are eligible for overtime at a rate of 1.5 times the base hourly rate for all hours worked in excess of 40 in a work week, or as required by state or local law. Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education and experience. Full-time employees are eligible to select from different benefits packages. Packages may include medical, dental, and vision benefits, health savings accounts with qualified medical plan enrollment, 10 paid days off, 3 days paid bereavement leave, 401(k) plan participation with employer match, life and disability insurance, commuter benefits, dependent care flexible spending account, accident insurance, critical illness insurance, hospital indemnity insurance, accommodations and reimbursement for work travel, and discretionary performance or recognition bonus. Sick leave and mobile phone reimbursement provided based on state or local law. Consent to Communication and Use of AI Technology: By submitting your application for this positionand providing your email address(es) and/or phone number(s), you consent to receive text (SMS), email, and/or voice communication whether automated(including auto telephone dialing systems or automatic text messaging systems), pre-recorded,AI-assisted, or individually initiated from Aditi Consulting, our agents, representatives, or affiliatesat the phone number and/or email address you have provided. These communications may include information about potential opportunities and information. Message and data rates may apply. Message frequency may vary. You represent and warrant that the email address(es) and/or telephone number(s) you provided to us belong to you and that you are permitted to receive calls, text (SMS) messages, and/or emails at these contacts.You also acknowledge and agree to Aditi Consulting LLC’s use of AI technology during the sourcing process, including calls from an AI Voice Recruiter. AI is used solely to gather data and does not replace human-based decision-making in employment decisions. Calls may be recorded. Consent is not a condition of purchasing any property, goods, or services. You may revoke your consent at any time by replying “STOP” to messages or by contacting [e-mail] . For information about our collection, use, and disclosure of applicant's personal information as well as applicants' rights over their personal information, please see our Privacy Policy #AditiConsulting # 26 - 06795