Codvo.ai

Solutions Engineer

• Develop and maintain the architecture blueprint across applications, data, cloud, integrations, and security.
• Define architectural principles, reference architectures, reusable patterns, and engineering standards.
• Establish governance models and ensure engineering teams adhere to architectural guidelines.
• Build multi year technology roadmaps aligned with business and digital transformation goals.
• Evaluate emerging technologies (AI/ML, IoT/Edge, automation, analytics, compute platforms) and drive POCs.
• Provide technical thought leadership to influence forward-looking architecture.
• Guide large-scale system architectures, cloud-native solution designs, and modernization initiatives.
• Ensure design alignment to availability, performance, reliability, cost, security, and compliance needs.
• Collaborate with product and engineering teams to translate business solutions into technical architectures.
• Architect enterprise data ecosystems including governance, pipelines, MDM, analytics, and AI.
• Lead cloud architecture across Azure/AWS/GCP, ensuring optimal design, scaling, and security.
• Define enterprise integration patterns—API-led, event-driven, microservices, and streaming.
• Partner with security engineering to embed zero-trust principles, IAM, encryption, and compliance frameworks.
• Ensure systems and data flows are designed with governance and risk management best practices.
• Engage with C level leaders, engineering directors, product owners, and business partners.
• Mentor engineering teams and elevate architectural maturity across the organization.
• Communicate architectural strategies, decisions, risks, and tradeoffs effectively.

Solution Architect

• Technical lead for the delivery team
• Translate architecture decisions into implementation tasks
• Review all technical deliverables
• Primary escalation point for integration issues
• Work closely with the on-site Data Scientist
• Maintain the detailed technical design document
• Design protocol bridge configuration for each site's BMS
• Design tag mapping pipeline
• Define the CI/CD pipeline for platform deployments
• Design monitoring and observability stack
• Conduct code reviews for all platform changes
• Define and enforce coding standards and expectations
• Own integration test strategy
• Troubleshoot production issues
• Run daily standups with the offshore team

Medical Reviewer

• Ensure clinical validity of ontology/guidelines and sign off on golden sets and edge-case adjudications.
• Approve ontology, definitions, and examples for the target procedure(s).
• Review and sign off “golden set” and high-risk label classes/events.
• Resolve escalated adjudication cases; document rationale when needed.
• Participate in periodic calibration reviews and guideline evolution.
• Resolve label disagreements from multi-rater overlap and QA escalations.
• Use side-by-side comparisons, guideline references, and evidence frames/clips to decide final truth.
• Classify disagreement causes (definition ambiguity, visibility limits, procedural variance, annotator error).
• Maintain adjudication logs and update guidelines/decision trees with approved changes.
• Escalate to clinical reviewer when needed; prepare concise packets for decision.
• Ensure adjudicated outputs feed back into training/calibration and pre-label improvement.

Clinical Reviewer, Surgeon, Part-Time, Contract

Risk

• Resolve label disagreements from multi-rater overlap and QA escalations.
• Use side-by-side comparisons, guideline references, and evidence frames/clips to decide final truth.
• Classify disagreement causes (definition ambiguity, visibility limits, procedural variance, annotator error).
• Maintain adjudication logs and update guidelines/decision trees with approved changes.
• Escalate to clinical reviewer when needed; prepare concise packets for decision.
• Ensure adjudicated outputs feed back into training/calibration and pre-label improvement.

Adjudicator – Disagreement Resolution, Guideline Governance

QA Engineer

• Protect dataset quality at scale by running sampling-based audits, enforcing quality gates, and ensuring every dataset release is audit-ready and meets acceptance thresholds.
• Execute sampling plans (stratified by label type, difficulty, site/surgeon/device, model confidence) for ongoing QA and release audits.
• Audit annotations against guidelines + ontology; score defects using standardized rubrics (severity, type, root cause).
• Run and validate quality gates prior to release: completeness/coverage checks schema/constraint checks (illegal combinations, temporal consistency, boundary rules) defect density and rework thresholds.
• Generate rework tickets with precise instructions; track closure and verify fixes.
• Partner with Annotation Lead to drive calibration actions (training refreshers, guideline clarifications, examples library).
• Maintain QA dashboards: defect rate, rework %, gate pass rate, audit cycle time, top error patterns by annotator/team/label type.
• Support release readiness: ensure required artifacts are complete for the Evidence Pack (QA results, sampling logs, sign-offs).
• Escalate systematic issues to Adjudication/Clinical Review (definition gaps, ambiguous classes, recurring edge cases).

QA Auditor, Sampling, Quality Gates, Release Readiness

• Approve ontology, definitions, and examples for the target procedure(s).
• Review and sign off “golden set” and high-risk label classes/events.
• Resolve escalated adjudication cases; document rationale when needed.
• Participate in periodic calibration reviews and guideline evolution.

Clinical Reviewer, Surgeon – Part-Time, Contract

Solution Architect – Oil & Gas

Artificial Intelligence

• Oversee end-to-end delivery across all RCM towers: Patient Access, Medical Coding, Charge Capture, Billing, AR, Denials, Cash Posting, and Provider Helpdesk.
• Lead high-performance operations across multi-site, multi-client delivery centers.
• Build scalable operational frameworks supporting rapid growth, high productivity, and cost efficiency.
• Establish and manage SLAs, KPIs, quality metrics, and performance governance across all accounts.
• Champion the adoption of AI, ML, GenAI, NLP, OCR, RPA, and workflow automation for RCM processes.
• Evaluate and deploy AI-enabled RCM platforms for denial prediction, coding automation, AR optimization, and intelligent document processing.
• Partner with data and engineering teams to implement dashboards, process mining, and predictive analytics.
• Drive continuous automation to reduce manual effort, accelerate turnaround times, and improve margins.
• Act as the senior delivery leader for enterprise healthcare clients including provider groups, MSOs, ASCs, hospitals, and payers.
• Ensure delivery excellence resulting in high NPS, retention, and revenue expansion.
• Collaborate with account management and sales to support renewals, expansions, and new solution offerings.
• Lead executive-level reviews, QBRs, and performance discussions with C-level stakeholders.
• Ensure adherence to HIPAA, CMS, coding guidelines, and payer compliance standards.
• Establish quality frameworks that meet regulatory and client expectations.
• Mitigate operational risks through strong controls, governance, and audit readiness.
• Drive certification programs (AAPC, AHIMA, CHFP) for staff.
• Lead large cross-functional teams including delivery, quality, training, and workforce management.
• Build leadership layers such as operations managers, senior managers, and process leads.
• Drive workforce planning, utilization, productivity improvement, and talent development.
• Promote a culture of accountability, learning, and innovation.

Head of Delivery – Healthcare RCM BPO, AI-Enabled

Project Manager

• Lead end-to-end project management for digital transformation initiatives
• Establish clear project charters and structured project plans
• Drive initiatives leveraging Azure, Google Cloud, and SAP ecosystems
• Manage cross-functional teams spanning IT, OT, data science, and business stakeholders

Project Manager, Data & AI, Oil & Gas

Data Engineer

• Architect & Build Data Pipelines: Design, construct, install, test, and maintain highly scalable data management systems and ETL/ELT pipelines.
• Integrate Diverse Data Sources: Develop processes to ingest and integrate high-volume, high-velocity data from SCADA systems, historians, DCS, PLC, and IoT sensors.
• Cloud Data Platform Development: Implement and manage data solutions on Microsoft Azure, leveraging services like Azure IoT Hub.
• Data Modelling & Warehousing: Design and implement data models optimized for time-series data from industrial assets.
• Enable Advanced AI: Build the data infrastructure to support AI/ML models for predictive maintenance and anomaly detection.
• Champion Master Data Management (MDM): Create a single source of truth for critical data domains.
• Ensure Data Quality & Governance: Implement data quality checks and monitoring to ensure accuracy and consistency.
• Embrace Industry Standards: Implement industry-specific standards for interoperability across sectors.
• Collaborate & Innovate: Work with cross-functional teams to understand data needs and deliver effective solutions.
• Automate & Optimize: Identify automation opportunities to improve data delivery and scalability.
• Security First: Maintain security best practices to protect sensitive data assets.

Data Engineer Lead, OT Data, Oil & Gas

Business Development Rep

• Drive New Business Growth in Oil & Gas by leading the energy-sector GTM strategy
• Shape, pitch, and close digital transformation and AI-driven modernization programs
• Build deep relationships with senior energy leaders
• Drive structured sales cadences
• Mentor presales consultants on Oil & Gas enterprise selling
• Collaborate with cross-functional teams to shape winning solutions

Sales Director – Oil & Gas, New Business Development

AI Engineer

• Build end-to-end RAG pipelines: smart chunking, hybrid retrieval, reranking, query rewriting.
• Implement LangGraph-based agentic workflows.
• Develop and optimize vector search systems.
• Architect and deploy AI microservices.
• Collaborate with architects and SMEs to translate use cases into AI systems.

RAG + Agentic AI Lead

Backend Engineer

• Apply design and coding best practices, including vectorization and object-oriented programming in Python.
• Ensure algorithms cover different scenarios with a focus on performance and scalability.
• Rapid ramp-up to work on deliverables within Scrum teams.
• Collaborate with cross-functional teams to integrate solutions into production systems.
• Utilize CI/CD, version control (Git), and automated testing in ML projects.

Python Engineer

Manager

• Create and maintain a comprehensive Master Test Plan
• Define test timelines and required resource capacity
• Standardize templates for test cases, test scripts, reviews, and bug reports
• Collaborate closely with Product Managers and Engineering Leads
• Create traceability between requirements and testing artifacts
• Analyze testing outcomes, metrics, and defect trends
• Lead a cross-functional QA team and foster a culture of quality

Solution Architect

Solution Architect

Clinical Reviewer, Surgeon, Part-Time, Contract

Adjudicator – Disagreement Resolution, Guideline Governance

QA Auditor, Sampling, Quality Gates, Release Readiness

Clinical Reviewer, Surgeon – Part-Time, Contract

Solution Architect – Oil & Gas

Head of Delivery – Healthcare RCM BPO, AI-Enabled

Solution Architect

Project Manager, Data & AI, Oil & Gas

Data Engineer Lead, OT Data, Oil & Gas

Sales Director – Oil & Gas, New Business Development

RAG + Agentic AI Lead

Python Engineer

Test Manager – Mexico, Colombia