Argos Multilingual

Analytics Engineer

• Partner with Sales and senior leadership on strategic customer opportunities with AI labs, model development teams, and enterprise AI organizations
• Lead discovery conversations with technical, research, product, operations, and executive stakeholders
• Translate customer requirements into solution designs, workflows, pilot plans, proposals, and implementation approaches
• Design solutions across model evaluation, multilingual data, speech/audio, transcription, expert review, post-training data, and quality workflows
• Support RFPs, RFIs, proposals, pricing assumptions, and Statements of Work
• Create customer-facing solution narratives, workflow diagrams, pilot structures, and technical explanations
• Collaborate with Delivery, Quality, Supply Chain, and Technology teams to ensure solutions are feasible, scalable, and commercially sound
• Support Sales-to-Delivery handoffs, including requirements, assumptions, risks, and success criteria
• Build reusable solution templates, scoping frameworks, and best practices for AI data and evaluation programs
• Track industry trends in model evaluation, benchmarking, RLHF, post-training data, agentic workflows, and multilingual AI

Senior Solutions Engineer, AI Data – Model Evaluation Solutions

IT Support

• Design scalable, distributed .NET systems optimized for processing massive volumes of multilingual textual and audio data
• Architect secure API integrations and middleware connecting .NET workflows with translation models, LLMs, and custom NLP pipelines
• Analyze existing tools used in Translation Management services
• Build a customizable suite of products or platform for individual customer needs with minimal configuration and fine-tuning
• Define technical standards, coding guidelines, and architectural blueprints for AI-assisted localization pipelines
• Lead technology teams
• Provide guidance and technical mentoring to developers
• Conduct thorough design and code reviews to ensure quality deliverables

Enterprise Software Architect – EMEA

Program Manager

• Lead strategic customer programs from onboarding through launch, delivery, scale, and steady-state operations.
• Own program plans, timelines, milestones, risks, dependencies, reporting, and customer communication.
• Partner with Quality, Supply Chain, Solutions, Sales, and leadership to ensure programs are clearly scoped and successfully delivered.
• Translate customer requirements into practical workflows, resource plans, delivery milestones, and operating models.
• Manage customer governance, including regular status updates, business reviews, issue tracking, and escalation management.
• Identify delivery risks early and drive mitigation plans across internal teams.
• Improve program documentation, delivery playbooks, reporting templates, and operational processes.
• Support complex AI data, multilingual, speech/audio, expert review, and managed services programs.
• Help ensure delivery commitments are operationally feasible, commercially aligned, and clearly communicated.
• Build strong relationships with customers and internal stakeholders.

Senior Program Director, AI Data Services

Data Scientist

• Own the quality strategy, operating model, and execution plan for AI Data Services.
• Build and standardize QA frameworks, audit models, scorecards, sampling approaches, and acceptance criteria.
• Define critical, major, and minor error classifications across different data workflows.
• Lead quality governance for strategic customer programs, including reporting, calibration, escalations, and remediation.
• Partner with Operations, Program Management, Supply Chain, Solutions, and Sales to ensure quality requirements are clearly understood and operationally feasible.
• Develop root cause analysis, corrective action, and continuous improvement processes.
• Build quality dashboards, customer-facing reporting, and internal quality performance views.
• Support the creation of SOPs, reviewer guidelines, calibration materials, and QA documentation.
• Help improve delivery consistency, reduce rework, and strengthen customer confidence.
• Mentor and guide QA managers, auditors, reviewers, and quality specialists as the team scales.

Head of Quality, AI Data Services – Americas, EMEA

• Build quality systems for AI data programs
• Design and manage quality frameworks for AI data and evaluation programs.
• Translate customer requirements into clear quality standards, rubrics, acceptance criteria, review processes, and KPIs.
• Build quality workflows that are practical, scalable, and trusted by customers as programs move from pilot to production.
• Identify quality risks early and work with delivery teams to resolve issues before they impact timelines, customer confidence, or program outcomes.
• Create repeatable quality processes across calibration, QA sampling, adjudication, reviewer performance tracking, and customer reporting.
• Lead evaluation, calibration, and QA processes
• Support quality operations across multilingual evaluation, speech/audio QA, transcription, data annotation, human preference evaluation, expert review, model response evaluation, coding evaluation, tool-use evaluation, and agent workflow evaluation.
• Create and improve rubrics, task instructions, reviewer guides, calibration exercises, golden datasets, and quality reporting templates.
• Lead calibration sessions with reviewers, annotators, quality specialists, delivery teams, and customer stakeholders.
• Define quality thresholds, error taxonomies, escalation rules, and corrective action plans.
• Monitor reviewer agreement, disagreement trends, error rates, contributor performance, and root causes of quality variance.
• Turn QA findings into practical improvements to instructions, training, tooling, staffing, and delivery workflows.
• Partner with customers and internal teams
• Act as a quality lead for strategic customer programs when needed.
• Support customer-facing quality readouts, pilot retrospectives, business reviews, escalations, and scale-up discussions.
• Provide clear, data-backed reporting that explains quality performance, risks, corrective actions, and next steps.
• Partner with Program Management, Supply Chain, Solutions, Sales, and Operations to ensure programs are set up for quality success from the start.
• Work with Supply Chain to define reviewer profiles, evaluator requirements, language requirements, domain expertise, onboarding needs, and performance expectations.
• Help determine when programs require expert reviewers, QA leads, language leads, technical reviewers, or specialized evaluation talent.
• Build and develop the quality function
• Build reusable quality assets such as calibration packs, QA reports, rubric libraries, error taxonomies, scorecards, and sample evaluation frameworks.
• Identify repeatable patterns across programs and turn them into standardized approaches that help the business scale.
• Improve visibility into quality performance across programs, reviewers, contributors, and workflows.
• Manage, coach, and support Quality Managers, Quality Leads, Quality Specialists, reviewers, or QA contributors assigned to Data Services programs.
• Coach team members on quality judgment, customer communication, escalation handling, reporting, and root-cause analysis.
• Identify hiring, training, and coverage needs as the Data Services business grows.
• Create a culture of quality ownership, accountability, and continuous improvement.
• Anticipate and communicate the needs identified for the team under your responsibility.
• Train, and support team members, advocate for upskilling and promote career growth.
• Be responsible for offering help to team members during increased workload periods, helping to avoid risks to Client deliveries due to their time demands (this includes finding cover for sickness and absence).

Senior Solutions Engineer, AI Data – Model Evaluation Solutions

Enterprise Software Architect – EMEA

Senior Program Director, AI Data Services

Head of Quality, AI Data Services – Americas, EMEA

Senior Manager, Data Quality – Evaluation