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Salary
≈ $140k – $269k per year (Estimated)
Location
In office (New York)
Seniority
Staff · 10+ years exp

Confirmed on the employer's own hiring board on Sep 27, 2026. First seen by Alion on Sep 26, 2026.

Overview
Company
Impact
Profile match
YO AI Labs is an artificial intelligence platform specializing in AI model training, evaluation, and data annotation services. Headquartered in San Francisco, California, United States, the company connects domain experts and remote specialists across the globe to review, test, and benchmark generative AI model outputs. Through its decentralized workforce solutions and structured evaluation workflows, it enables frontier technology developers to enhance the accuracy, safety, and reliability of next-generation artificial intelligence systems.

Role Name : Technical Consultant, Pharma (Business Translator)

Location : New York, USA

Experience: 10 -15 Years

Role Overview: The Technical Consultant role is responsible for end-to-end client management, program management, business growth, and client success by ensuring solutions are scalable, secure, cost-efficient, and aligned with modern data engineering, analytics, and AI/ML best practices. The consultant will partner with engineering teams, data product owners, and business stakeholders to establish architectural standards, design cloud-native data platforms, and guide technical execution across complex programs.

Roles and Responsibilities:

  • Drive senior client workshops, problem framing, and solution framing
  • Lead end-to-end client advisory, opportunity creation, and demand generation
  • Engage with business and technical teams to align architecture with business requirements
  • Support RFP and RFI responses and architectural evaluations
  • Experience with Life Sciences datasets, migration, and modernization
  • Understanding of operational layers L1, L2, and L3, along with ontology and context layers
  • Define and enforce data modeling, metadata, lineage, and quality standards
  • Implement CI/CD pipelines and monitoring frameworks
  • Ensure architectures support observability, reliability, and operational excellence
  • Architect end-to-end solutions on AWS and Databricks
  • Define architectural standards, patterns, and best practices
  • Review and guide solution designs for scalability, performance, and security
  • Evaluate technology options and recommend long-term architectural strategies
  • Translate business and analytical requirements into scalable data models
  • Assess current-state data architectures and define future-state models
  • Design scalable data models for analytical and operational workloads
  • Demonstrate strong understanding of metadata, lineage, data quality, and governance frameworks
  • Be familiar with distributed compute paradigms and cloud-native modeling patterns

Required Qualifications:

  • At least 10+ years of experience in AI, software development, data engineering, or data architecture along with
  • 5+ years of Life Sciences consulting experience
  • Experience driving modernization initiatives for AI products with AI foundations, governance, operational layers, and context layers
  • Strong experience with Databricks, DBT Core or Cloud, Python, Spark, SQL, distributed compute paradigms including in-memory, distributed, and MPP architectures, and Data Vault 2.0 including automate_dvDeep knowledge of AWS services including S3, Glue, Redshift, EMR, DynamoDB, Lambda, Athena, and Kinesis
  • Experience leading architecture across multi-team onsite and offshore delivery models
  • Executive presence to lead VP and Executive Director-level meetings and steering committees independently
  • Ability to drive thought leadership, technical visioning, workshops, and client success initiatives
  • Life Sciences experience preferred
  • Ability to translate complex analytical requirements into scalable architectures including data models, ETL pipelines, and consumption layers
  • Experience designing and deploying dashboards and self-service analytics on relational and non-relational databases
  • Strong understanding of CI/CD, DevOps, static code analysis, and test-driven development
  • Experience with cloud migration patterns and modern data platform design
  • Experience defining data standards, metadata models, lineage, quality rules, and governance patterns
  • Experience implementing logging, monitoring, observability, and cost optimization frameworks
  • Experience driving enterprise data platform adoption and modern data practices
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