Lead business growth initiatives and drive revenue within the MedTech domain by managing key client relationships and strategic partnerships. Develop and execute sales plans to expand market presence across hospitals, healthcare providers, and life sciences organizations.
Own the top-of-funnel growth and sourced pipeline by designing an AI-powered demand engine. Responsible for ICP definition, multi-touch outbound campaigns, and aligning marketing efforts with sales to drive qualified meetings and revenue.
Design and develop internal CLI tools, automation frameworks, and dashboards to enhance the efficiency of data and machine learning platforms. Automate workflows on Databricks and implement robust testing frameworks for ETL and ML inference pipelines.
Collaborate with Data Science teams to implement and integrate ML algorithms into production code. Focus on ensuring performance, scalability, and the application of coding best practices within Scrum teams.
Design and build AI agent pipelines and RAG systems using graph-based workflows and vector search architectures. Develop end-to-end product features including scalable FastAPI backends and polished React/Next.js frontends.
Lead a scrum team in designing and evolving end-to-end architecture for software deployed on edge devices and integrated with backend SaaS services. Manage technical dependencies, lead system integrations, and provide guidance to engineers to balance velocity and quality.
Coordinate QA activities across the Neio AI product suite, including planning, work allocation, and status reporting. Drive automation framework improvements and guide junior QA resources on test coverage and standards.
Design and execute comprehensive test scenarios for AI-powered products, focusing on UI and API automation. Validate AI-driven workflows including chatbot responses, document extraction, and RAG-based outputs.
Coordinate QA activities across the Neio AI product suite, including planning, work allocation, and status reporting. Lead the automation framework improvements and guide junior QA resources on test coverage and standards.
Lead the vision, strategy, and end-to-end development of the NeIO GIS product line, focusing on AI-powered geospatial solutions. Drive go-to-market strategies and oversee the implementation and delivery of these solutions for enterprise clients.
The SME provides deep domain expertise in retail operations to translate business needs into actionable strategies and technical requirements for AI and technology solutions. They partner with product and engineering teams to validate features and optimize operational processes across the supply chain and merchandising.
The role involves designing and implementing end-to-end ML and Deep Learning pipelines for regression and industrial control use cases. Responsibilities include optimizing neural network architectures and collaborating with cross-functional teams to integrate solutions into production.
The role involves designing and implementing end-to-end ML and Deep Learning pipelines for regression and industrial control use cases. Responsibilities include optimizing neural network architectures and collaborating with cross-functional teams to integrate solutions into production.
Design and develop RESTful APIs using FastAPI and optimize relational data layers with complex T-SQL queries. Collaborate with cross-functional teams to define API contracts and maintain comprehensive automated test suites.
Design, build, and scale enterprise-grade AI agents using Microsoft Copilot Studio and agentic orchestration. Integrate these agents with enterprise systems via Power Automate and APIs to drive business value.
Develop and maintain the Python codebase for the core automation engine, focusing on data ingestion, standardization, and matching algorithms. Build responsive frontend components using React.js and create complex report pipelines for Excel and PDF outputs.
Develop and deploy ML models and LLM-based solutions to predict product outcomes based on specific attributes. Transform an existing AI agent into a data-driven prediction engine and integrate LLM capabilities for improved reasoning.
Design and maintain the core automation engine for data ingestion, standardization, and matching logic. Develop automated report generation systems for Excel and PDF outputs while optimizing database queries.
Develop and maintain the Python codebase for the core automation engine, focusing on data ingestion, standardization, and matching algorithms. Build responsive frontend components using React.js and create complex report pipelines for Excel and PDF outputs.
Design and maintain the core automation engine for data ingestion, standardization, and matching logic. Develop automated report generation systems for Excel and PDF outputs while optimizing database queries.
Develop and maintain the Python codebase for a core automation engine, focusing on data ingestion, standardization, and matching algorithms. Build responsive frontend components using React.js and create complex report pipelines for Excel and PDF outputs.
Design and implement intelligent exception resolution capabilities by integrating LLMs like Claude and OpenAI into a financial reconciliation platform. Develop robust API integrations and human-in-the-loop workflows to ensure financial accuracy and auditability.
Design and develop RESTful APIs using FastAPI and optimize relational data layers with complex T-SQL queries. Collaborate with cross-functional teams to define API contracts and maintain comprehensive automated test suites.
Lead the end-to-end lifecycle of B2B AI and Agentic platforms, from product vision and roadmap execution to GTM strategy. Drive enterprise client success through requirement discovery, solutioning, and high-quality product delivery.
Design, develop, and optimize machine learning and deep learning models using PyTorch while building end-to-end ML pipelines. Collaborate with cross-functional teams to deploy scalable AI solutions on AWS and maintain MLOps workflows.
Design, develop, and maintain scalable data pipelines using Databricks and Python while managing data governance via Unity Catalog. Collaborate with cross-functional teams to optimize ETL workflows and deliver high-quality data solutions.
Design, build, and maintain Databricks data pipelines while operationalizing machine learning models for production environments. Ensure data reliability and quality through robust monitoring, validation, and the implementation of MLOps best practices.
Design, build, and maintain Databricks data pipelines while operationalizing machine learning models for production. Ensure data reliability and quality through robust monitoring, observability, and MLOps best practices.
The DevOps Administrator will manage cloud infrastructure, CI/CD pipelines, and system reliability on Azure. They are responsible for incident response, environment stability, and enforcing security best practices across customer-facing applications.
The IT Project Manager will own end-to-end project delivery, including planning, scheduling, and execution for AI/ML and data-driven solutions. They will also manage stakeholder communication, drive Agile ceremonies, and ensure alignment between product roadmaps and engineering teams.
You will lead a team of DevOps engineers to ensure the seamless operation of platforms and applications. Responsibilities include implementing infrastructure, automating deployments, and optimizing systems for performance and reliability.
The Product Owner will own the vision, roadmap, and strategy for the Financial Reconciliation product line, identifying automation opportunities and driving execution. They will also lead client implementations and manage human-in-the-loop operations to ensure quality and efficiency.
The Product Owner will own the vision, roadmap, and strategy for the NeIO GIS Coworker product line, focusing on identifying high-value use cases across various GIS workflows. Key duties include defining the product backlog, driving execution with engineering teams, and leading Go-To-Market activities and client delivery for enterprise solutions.
The role is responsible for developing, integrating, monitoring, and supporting industrial automation and data management solutions primarily using AVEVA System Platform 2023, covering end-to-end implementation from device data acquisition to visualization dashboards. Key tasks include configuring AVEVA applications, integrating BMS/EPMS systems, implementing alarm management via UOC, and utilizing n8n for workflow automation and AI-driven enhancements.
The role is responsible for developing, integrating, monitoring, and supporting industrial automation and data management solutions primarily using AVEVA System Platform 2023, covering end-to-end implementation from device data acquisition to visualization and operational dashboards. Key tasks include configuring AVEVA applications, integrating BMS/EPMS systems, implementing alarm management via UOC, and utilizing n8n for workflow automation and AI-driven enhancements.
The role involves owning the data pipeline from BMS ingestion through the analytics layer, focusing on data reliability, quality, and real-time streaming infrastructure for ML models. Key tasks include building ingestion bridges for industrial protocols (OPC-UA, BACnet, MQTT) and managing data storage solutions like TimescaleDB and MinIO/S3.
The Senior Product Manager will own the end-to-end lifecycle for AI-led and Agentic platforms, encompassing product strategy, delivery, Go-To-Market execution, and client success management. Key duties involve leading product vision, managing the backlog, ensuring release readiness, defining GTM strategy, and supporting enterprise sales engagements.
The Solution Architect is responsible for designing end-to-end technology solutions that align with business objectives, scalability needs, and architectural best practices. This role involves guiding large-scale system architectures, defining enterprise data and cloud ecosystems, and establishing governance models for engineering standards.
The Solution Architect acts as the day-to-day technical lead, translating architecture decisions into implementation tasks, reviewing all technical deliverables, and serving as the primary escalation point for integration issues. Key duties include designing technical documentation, defining protocol bridge configurations, designing the tag mapping pipeline, and defining the CI/CD and monitoring stacks.
The role involves model development, maintaining training pipelines, and building the analytics backend, working closely with an on-site Data Scientist for context and feedback. Key tasks include improving simulation engines, running training pipelines, implementing retraining triggers, and developing evaluation frameworks.
The primary role involves ensuring the clinical validity of ontologies and guidelines by approving definitions, reviewing and signing off on 'golden sets' and high-risk labels, and resolving escalated adjudication cases with documented rationale. A secondary role focuses on converting multi-rater disagreements into defensible ground truth by using evidence and updating decision trees.
The primary mission is to achieve high-volume, high-accuracy annotations by strictly verifying and correcting pre-labels according to established guidelines. This involves tagging temporal phases, tools, anatomy, and events, while efficiently using annotation tool features.
The role owns the end-to-end delivery of a high-throughput, clinically defensible surgical video annotation program, focusing on driving automation-first workflows, quality assurance, and timely dataset releases. This includes standing up the annotation factory, operationalizing clinical ontologies, implementing quality systems, and managing dataset release discipline.
The Solution Architect is responsible for designing end-to-end technology solutions aligning with business objectives, scalability, and architectural best practices, while maintaining hands-on technical depth. Key duties include developing architecture blueprints, defining standards, building technology roadmaps, and leading cloud and data ecosystem designs.
The Solution Architect is responsible for designing end-to-end technology solutions that align with business objectives, scalability needs, and architectural best practices. This role involves defining architecture strategy, building technology roadmaps, leading cloud and data architecture, and ensuring security and compliance across systems.
The Engagement Lead will collaborate closely with internal teams and clients to ensure seamless customer experiences, driving adoption and success while maintaining high Customer Satisfaction (CSAT) and Net Promoter Score (NPS). This role involves managing strategic communications up to the CxO level, overseeing legal and contractual requirements, and proactively managing risks to ensure smooth project delivery.
The role involves architecting and building highly scalable data management systems and ETL/ELT pipelines, integrating high-volume data from operational technology sources like SCADA and historians into the Microsoft Azure cloud platform. Key duties include developing data models optimized for time-series data and building the infrastructure to support AI/ML models for operational optimization.
The Project Manager will lead end-to-end digital transformation initiatives, overseeing planning, execution, and delivery using Data, AI, and modern cloud technologies to ensure alignment with business goals and industry demands. Key duties include managing cross-functional teams, driving solution delivery leveraging Azure and Databricks, and ensuring project outputs translate into measurable business outcomes like efficiency gains.
The Sales Director will be responsible for driving new business growth in the Oil & Gas sector by building an $8-10M qualified pipeline and closing $3-4M in new annual revenue through shaping and pitching digital transformation and AI modernization programs. This role also involves engaging senior energy leaders, running disciplined sales operations, and leading/coaching the Presales team.
The Product Owner will define the vision and roadmap for AI-powered platforms and assistants, focusing on problem-first prioritization and translating complex capabilities into measurable business value. Key duties include leading backlog management, defining success metrics like accuracy and adoption, and bridging communication between business stakeholders and engineering teams.
The Test Manager will create and maintain a comprehensive Master Test Plan, define test timelines, and standardize testing templates and quality metrics across projects. Responsibilities also include leading the QA team, fostering technical capabilities, and driving continuous improvement based on testing outcomes.
The Test Manager will create and maintain a comprehensive Master Test Plan, define test timelines, standardize templates for quality artifacts, and establish test strategies in collaboration with Product Managers and Engineering Leads. They will also lead a cross-functional QA team, focusing on building technical capabilities and fostering a culture of quality.
The Senior Technical Lead will act as the technical lead for a scrum team, focusing on building software deployed on edge devices and ensuring alignment with enterprise architecture. Responsibilities include leading integration with internal teams, participating in scrum activities, and producing clear technical documentation.
Design and develop applications on the MERN Stack while mentoring team members. Implement CI/CD pipelines and ensure data quality and security compliance.
The Solutions Architect will lead the design and delivery of end-to-end data and analytics solutions on the Databricks platform, translating complex business needs into scalable, secure, and cost-efficient data lakehouse architectures. Responsibilities include architecting data pipelines, enabling data science/ML workflows, ensuring data governance, and leading customer-facing activities like workshops and solution demos.
The Data Scientist will perform advanced data analysis and develop predictive models for industrial applications. They will collaborate with cross-functional teams and support on-site installation and commissioning activities as required.
The Project Manager will lead digital transformation initiatives, overseeing project management from scoping to execution while ensuring alignment with business goals. They will manage cross-functional teams and drive initiatives leveraging modern technologies.
The Data Science Lead will design, develop, and deploy production-grade ML and DL models, focusing on time-series data and predictive analytics. They will also implement LLM-powered applications and develop workflows for Agentic AI systems.
The Machine Learning Engineer will work closely with the Data Science team to develop and implement ML algorithms into production code. They will ensure that algorithms are optimized for performance and scalability while collaborating with cross-functional teams.
Lead a high-performing engineering team to build intelligent, scalable systems leveraging AI and modern frameworks. Ensure delivery excellence and high engineering standards while mentoring and coaching team members.
The role involves building production-grade retrieval systems and multi-agent workflows. You will also work on document pipelines and model orchestration to enhance Codvo’s AI applications.
The Senior Full Stack Engineer will be responsible for building scalable data platforms and solving complex data challenges. This role involves both frontend and backend development, focusing on enterprise AI projects.
The Senior Generative AI Engineer will be responsible for building, optimizing, and deploying RAG pipelines and working with agentic frameworks. The role involves solving complex data challenges using creativity and cutting-edge technology.
You will own the vision, roadmap, and delivery of intelligent, AI-native products & solutions. This role involves defining a problem-first roadmap, leading product development, and ensuring compliance and observability.
Define and execute the go-to-market influence marketing strategy for Codvo.ai’s AI and product portfolio. Lead the creation of a full-spectrum influence strategy leveraging various channels to shape Codvo.ai’s presence across key verticals.
The Engineering Manager will lead and mentor engineering teams, ensuring the delivery of complex data solutions. They will be responsible for managing technical risks and fostering a collaborative environment.
Lead end-to-end project management for digital transformation initiatives, ensuring alignment with business goals and regulatory requirements. Oversee projects involving data platforms, AI/ML, and advanced analytics while managing cross-functional teams.
The Senior AI Engineer will lead the design and deployment of integrated GIS-Power BI solutions, focusing on land analytics and operational KPIs in the oil & gas sector. Responsibilities include architecting ESRI-based GIS solutions and integrating GIS data with Power BI for geospatial analytics.
The GIS Web Developer will implement new spatial query types, optimize ArcGIS REST API performance, and create interactive map visualizations. They will also connect GIS features with business data and build efficient data pipelines.
The GIS Web Developer will implement new spatial query types, optimize ArcGIS REST API performance, and create interactive map visualizations. They will also connect GIS features with business data and build efficient data pipelines.
The Full Stack Engineer will design and develop applications on the MERN Stack and mentor team members towards common objectives. They will also implement CI/CD pipelines and ensure data quality and security compliance.
Lead the design, implementation, and optimization of enterprise-scale Azure data platform solutions. Establish best practices for data engineering and analytics while driving modern data architecture initiatives.
The Product Owner will own the vision, roadmap, and delivery of enterprise-grade data platforms and BI experiences, ensuring that fragmented data is transformed into actionable products. Responsibilities include defining the roadmap, managing product development, and ensuring compliance with governance standards.
Lead the design, implementation, and optimization of enterprise Snowflake data platform solutions. Establish scalable analytics capabilities and drive cloud-native data architecture initiatives.
The Product Owner will define the vision and roadmap for AI-powered platforms, ensuring the delivery of intelligent products that enhance enterprise workflows. They will lead product development, manage dependencies, and drive continuous improvement through measurement and iteration.
The Data Quality Engineer will design and implement robust data quality frameworks to ensure data accuracy, consistency, and reliability across data platforms. Responsibilities include developing data quality checks, collaborating with teams to resolve data issues, and automating reporting mechanisms.
The Product Owner will define the vision and roadmap for AI-powered platforms and assistants, ensuring they deliver measurable business value. They will lead product development, manage dependencies, and drive continuous improvement through metrics and experimentation.
The Product Owner will own the vision, roadmap, and delivery of enterprise-grade data platforms and BI experiences. Responsibilities include defining the roadmap, driving product leadership, and ensuring governance and compliance.
Lead the design, implementation, and optimization of enterprise Snowflake data platform solutions. Establish scalable analytics capabilities and drive cloud-native data architecture initiatives.
The Practice Lead will define and execute the strategic roadmap for the Data & AI practice, focusing on Lakehouse architecture and cloud-native modernization. They will lead a cross-functional team to deliver high-impact data solutions across various industries.
The Technical Lead will own and drive the technical execution of cloud, AI, and IoT-based retail modernization initiatives. They will also manage integrations and oversee the implementation of scalable Azure-native architectures.
The Practice Lead will define and execute the strategic roadmap for the Data & AI practice, focusing on Lakehouse architecture and cloud-native modernization. They will lead a cross-functional team to deliver high-impact solutions that combine technical excellence and cost efficiency.
Engage directly with customers to design, develop, and deploy AI-based enterprise applications. Continuously identify technical risks and gaps while enhancing customer applications.
The CRA Practice Lead will establish and scale a secure software development and certification practice aligned with the EU Cyber Resilience Act. This role involves leading a multidisciplinary team to ensure software products meet high standards of cybersecurity and regulatory readiness.
The Technical Lead will drive the technical execution of cloud, AI, and IoT-based retail modernization initiatives. They will oversee the development of scalable Azure-native architectures and ensure successful implementation across various retail use cases.
Lead engagement strategy and execution across assigned client accounts while ensuring timely delivery of performance goals and customer satisfaction. Build and maintain strong client relationships and identify opportunities for upselling and cross-selling.
As Senior Lead – AI Engineering, you will own the end-to-end architecture, delivery, and optimization of enterprise RAG and agentic systems. You will lead a small team of AI engineers to build and deploy LangGraph, Haystack, and FastAPI-based pipelines that extract, enrich, and reason over unstructured data.
As Senior Lead – AI Engineering, you will own the end-to-end architecture, delivery, and optimization of enterprise RAG and agentic systems. You will lead a small team of AI engineers to build and deploy LangGraph, Haystack, and FastAPI-based pipelines that extract, enrich, and reason over unstructured data.
Lead the design and delivery of end-to-end data and analytics solutions on the Databricks platform. Collaborate with cross-functional teams to translate complex business needs into scalable and secure data architectures.
The Data Scientist will design, build, and validate predictive models for connected vehicle analytics, focusing on driver behavior analysis and vehicle health monitoring. They will analyze complex datasets to uncover actionable insights and collaborate with teams to integrate these insights into decision-making systems.
The Senior AI Engineer will lead the design, development, and implementation of robust and scalable pipelines and backend systems for Generative AI applications. This includes orchestrating data flow, integrating AI services, and ensuring the smooth operation of backend infrastructure.
The Senior Lease Analyst will be responsible for validating lease obligations and reconciling ownership records. They will also prevent royalty revenue leakage and build defensible audit trails for regulatory agencies.
Develop and execute strategic partnership plans with leading Cloud Service Providers and Independent Software Vendors. Own day-to-day partner engagement and identify co-innovation opportunities.
As Senior Lead – AI Engineering, you will own the end-to-end architecture, delivery, and optimization of enterprise RAG and agentic systems. You will lead a small team of AI engineers to build and deploy LangGraph, Haystack, and FastAPI-based pipelines that extract, enrich, and reason over unstructured data.
The Engagement Lead will lead engagement strategy and execution across assigned client accounts, ensuring timely delivery of performance goals and customer satisfaction. They will build and maintain strong client relationships while identifying upsell and cross-sell opportunities.
The Data Scientist will design, build, and validate predictive models for connected vehicle analytics, focusing on driver behavior analysis and vehicle health monitoring. They will also analyze complex datasets to uncover actionable business insights and collaborate with teams to operationalize models.
