C# Developer (SSE)

Docusign Developer

Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Solution Engineer - Security

 IIAD / SAD / LAD Artificial Intelligence Engineer

Key Account and E-Commerce Manager

Lead AI Engineer

Senior QA Automation Engineer

Responsibilities: <ul><li>Develop distributed system architecture and system integration&nbsp;&nbsp;</li><li>Design event-driven applications leveraging microservices architecture on cloud platform&nbsp;</li><li>Carry out Model and assess complex IT solutions&nbsp;&nbsp;</li><li>Work closely with platform engineers and other IT professionals to choose compatible design solutions&nbsp;</li><li>Manage and comply with release management process&nbsp;</li><li>Analyze the scope and expected organizational impact of information systems&nbsp;</li><li>Evaluate existing systems and provide advice on how to meet organizational requirements&nbsp;</li><li>Ensure that the technical components of the project are in sync with the business needs of the organization&nbsp;</li><li>Ensure that information systems are secure from threat&nbsp;</li><li>Provide advice on project design, project costs, and expected benefit&nbsp;</li><li>Identifies technical debt and proactively recommends alternatives or improvements&nbsp;</li></ul> Requirements: <ul><li>University degree in Computer Science, Computer Engineering or related subjects preferred&nbsp;&nbsp;</li><li>8+ years of work experience building applications&nbsp;</li><li>Advanced understanding of IT infrastructure and enterprise architectures&nbsp;</li><li>Proven experience with microservices-based architecture&nbsp;</li><li>Proficiency in coding with modern programming languages such as C#, Python, or Node.js&nbsp;</li><li>API-first development experience&nbsp;</li><li>Experience with Cloud Computing (Azure preferable)&nbsp;</li><li>Extensive expertise in any modern document-oriented database, with a preference for MongoDB&nbsp;</li><li>Experience in developing components for Event-Driven Architecture, with a minimum of production-level experience using Event Hubs or Event Grid (or similar technologies like Kafka)&nbsp;</li><li>Experience working in an agile environment with a focus on engineering practices like testing, continuous integration, etc.&nbsp;</li><li>Good knowledge of virtualization&nbsp;&nbsp;</li><li>Analytics mindset with critical thinking and problem-solving skills&nbsp;</li><li>Fine knowledge of industry trends and emerging technologies&nbsp;</li><li>Fluent in English&nbsp;</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain integrations with DocuSign CLM+ and eSignature APIs.</li><li>Implement and customize contract lifecycle management workflows.</li><li>Develop robust backend components using Java and C# to support business logic and integrations.</li><li>Work with XML and XSLT for document transformations and data interchange.</li><li>Build and manage stored procedures, packages, and triggers using Oracle PL/SQL.</li><li>Utilize Eclipse for Java development and Visual Studio for C# development.</li><li>Configure and support CI/CD pipelines using Azure DevOps.</li><li>Collaborate closely with business analysts, architects, QA, and infrastructure teams.</li><li>Troubleshoot and resolve integration and application issues across environments.</li><li>Create and maintain technical documentation and contribute to best practices.</li></ul> Requirements: <ul><li>8+ years of experience in enterprise application development.</li><li>Proficiency with DocuSign CLM+ (contract templates, workflow design, API integration).</li><li>Strong experience with DocuSign eSignature API and embedded signing flows.</li><li>Solid programming skills in Java and C#.</li><li>Expertise in XML and XSLT for document parsing and transformation.</li><li>Strong knowledge of Oracle Database and PL/SQL development.</li><li>Experience using Eclipse IDE and Visual Studio for software development.</li><li>Hands-on experience with Azure DevOps for version control, CI/CD pipelines, and environment management.</li><li>Strong analytical, communication, and problem-solving skills.</li></ul>

Responsibilities: <ul><li>We are seeking a Solutions Engineer - Artificial Intelligence (AI) Practitioner to join our dynamic sales team. As an SE (AI Practitioner), you will consult and drive the adoption of our AI solutions across various industries.</li><li>You will identify potential clients, understand their specific needs, and provide tailored AI solutions that enhance their business operations.</li><li>This role requires a deep understanding of AI technologies, real world deployment experience and expert capability to relay business and technical concepts to a diverse audience.</li><li>The Cloud and AI Infrastructure team is responsible for helping customers change their business using Client technology in the data center and on cloud. The team works with customers, partners and engineering teams to take customer problems and turn them into business advantage.</li></ul> Requirements: Minimum Qualifications: <ul><li>10+ years of technology consulting experience (preferably in systems, software, data, analytics and AI).</li><li>Good understanding of programming/scripting languages</li><li>Ability to provide detailed and consumable documentation and standard methodologies for deployment around application acceleration, automation/management efficiencies, enterprise, and AI/ML solutions.</li><li>Be able to develop and showcase real world examples of how AI technology can help businesses thrive and solve problems.</li><li>Excellent presentation skills – ability to value-sell and deliver engaging workshops to both technical and non-technical audiences on AI and/or infrastructure topics. Preferred</li><li>Bachelors Degree in Computer Science, Computer Engineering, Electrical Engineering, or related field. Advanced degree in Data Science is a plus.</li><li>Experience with AI relevant infrastructure, including Networking (InfiniBand and RoCE), Storage (FC, IP and scale out) and AI accelerators (GPUs etc).</li><li>In-depth understanding of AI models, including but not limited to GPT, Llama, Resnet or similar.</li><li>Experienced with data storage and management (SQL, NOSQL, Vector, BigQuery etc) and AI/ML frameworks (scikit-learn, TensorFlow, PyTorch, Jupyter, NIMS and NVAIE etc).</li><li>Expertise in training and fine-tuning AI models on premise or in cloud environments.</li><li>Familiarity with containerization (k8 etc).</li></ul>

Responsibilities: <ul><li>Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.&nbsp;</li><li>Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.&nbsp;</li><li>Implement automated retraining, drift detection, and re-deployment of ML models.&nbsp;</li><li>Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.&nbsp;</li><li>Implement model monitoring, observability, and alerting across accuracy, latency, and cost.&nbsp;</li><li>Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.&nbsp;</li><li>Ensure pipelines are secure, compliant, and cost-optimized.&nbsp;&nbsp;</li><li>Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance .&nbsp;</li><li>Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.&nbsp;</li><li>Stay current with the latest ML research and apply new tools pragmatically to production systems.&nbsp;</li><li>Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.&nbsp;</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD is a plus).&nbsp;</li><li>5+ years of experience in machine learning engineering, MLOps, or large-scale AI/DS systems.&nbsp;</li><li>Strong foundations in data structures, algorithms, and distributed systems.&nbsp;</li><li>Proficient in Python (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.) and SQL.&nbsp;</li><li>Hands-on experience building and deploying ML models at scale in cloud environments (GCP Vertex AI, AWS SageMaker, Azure ML).&nbsp;</li><li>Experience with containerization (Docker, Kubernetes) and orchestration (Airflow, TFX, Kubeflow).&nbsp;</li><li>Familiarity with CI/CD pipelines, infrastructure-as-code (Terraform/Helm), and configuration management.&nbsp;</li><li>Experience with big data and streaming technologies (Spark, Flink, Kafka, Hive, Hadoop).&nbsp;</li><li>Practical exposure to model observability tools (Prometheus, Grafana, EvidentlyAI) and governance (WatsonX)&nbsp;</li><li>Strong understanding of statistical methods, ML algorithms, and deep learning architectures.&nbsp;</li></ul>

Responsibilities: <ul><li>Dashboard Design and Development: Design, develop, and maintain interactive and user-friendly dashboards in PowerBI and Looker, focusing on clarity, performance, and data accuracy.&nbsp;</li><li>Data Lake Integration: Connect to and leverage data from various data lake sources on GCP, ensuring seamless data flow for visualization purposes.&nbsp;</li><li>Semantic Model Development: Develop and maintain robust semantic models in Looker (LookML) and PowerBI, ensuring data consistency, accuracy, and ease of use for reporting and analysis. This includes defining dimensions, measures, relationships, and calculations.&nbsp;</li><li>Machine Learning and GenAI Visualization: Create compelling visualizations to effectively communicate the results, performance, and insights derived from machine learning models and GenAI applications. This may involve visualizing model predictions, feature importance, natural language processing outputs, and other relevant data.&nbsp;</li><li>GCP Expertise: Utilize your strong understanding of GCP services to access, process, and prepare data for visualization. This may involve working with services such as BigQuery, Cloud Storage, and potentially data engineering pipelines built on GCP.&nbsp;</li><li>Collaboration: Partner closely with data scientists, data engineers, product managers, and business stakeholders to understand their data visualization needs and translate them into effective visual solutions.&nbsp;</li><li>Requirements Gathering: Elicit and document visualization requirements from various stakeholders, ensuring alignment with business objectives.&nbsp;</li><li>Performance Optimization: Optimize dashboard and visualization performance to ensure fast load times and efficient data rendering.&nbsp;</li><li>Data Quality Assurance: Ensure the accuracy, consistency, and reliability of data presented in visualizations.&nbsp;</li><li>Best Practices and Standards: Establish and enforce data visualization best practices and standards across the organization.&nbsp;</li><li>Training and Support: Provide guidance and support to other team members on data visualization tools and techniques.&nbsp;</li><li>Continuous Learning: Stay up to date with the latest trends and advancements in data visualization, PowerBI, Looker, GCP, and related technologies, particularly in the context of AI/ML.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s or master’s degree in computer science, Data Science, Statistics, Information Systems, or a related field.&nbsp;</li><li>Minimum of 3 years of experience as a Visualization Expert, Data Visualization Engineer, or a similar role.&nbsp;</li><li>Proven expertise in designing and developing interactive dashboards and reports using PowerBI and Looker.&nbsp;</li><li>Strong experience in connecting to and working with data lakes, preferably on the Google Cloud Platform (GCP).&nbsp;</li><li>Solid understanding and hands-on experience in developing semantic models, particularly with LookML in Looker and data modeling within PowerBI.&nbsp;</li><li>Preferable experience in creating visualizations specifically for machine learning and GenAI applications, understanding the nuances of presenting model outputs and insights.&nbsp;</li><li>Proficiency in SQL for data extraction and manipulation.&nbsp;</li><li>Familiarity with data warehousing concepts and data modeling techniques.&nbsp;</li><li>Experience with data preparation, ELT (preferred) / ETL processes.&nbsp;</li><li>Strong analytical and problem-solving skills with the ability to interpret complex data.&nbsp;</li><li>Excellent communication and presentation skills, with the ability to convey technical information to both technical and non-technical audiences.&nbsp;&nbsp;</li><li>Ability to work independently and collaboratively in a fast-paced environment.&nbsp;&nbsp;</li><li>Strong portfolio showcasing your data visualization skills and experience.&nbsp;</li></ul>

Responsibilities: <ul><li>As a key player in the team, you will have the opportunity to influence the security landscape by crafting tailored solutions that address specific customer needs.</li><li>This role offers the excitement of working with cutting-edge technology and the fulfillment of building long-lasting relationships with customers.</li><li>Provide guidance and assist account teams in building solutions to address specific customer security needs.</li><li>Understand business requirements and translate them into technical solutions.</li><li>Create, present, and document technical solutions to customers, partners, and prospects.</li><li>Lead technical consulting and upper-level management presentations.</li><li>Drive major account opportunities while enabling local account teams to maintain long-term ownership.</li></ul> Requirements: Minimum Qualifications <ul><li>Minimum of 4 years of technical sales or pre-sales experience with 2+ years in Security specialization (Email Security, IDS/IPS, AV, Firewall, Advanced Malware Protection).</li><li>Bachelors degree in Cybersecurity, Computer Science, or a related field.</li><li>Proven track record of successful quota achievement.</li><li>Strong knowledge of cybersecurity concepts, technologies, and best practices.</li><li>Industry certifications such as CISSP, CISM, or CCSP are preferred..</li></ul> Preferred Qualifications <ul><li>Excellent presentation and interpersonal skills.</li><li>Commercial awareness and strong communication skills.</li><li>Highly motivated self-starter who excels without day-to-day management.</li><li>Experience with Client security technologies and programming languages such as UNIX shell, Perl, or C.</li><li>Willingness to travel and work from a home office. As a key player in the team, you will have the opportunity to influence the security landscape by crafting tailored solutions that address specific customer needs.</li></ul>

Responsibilities: Agentic AI Development:&nbsp;&nbsp; <ul><li>Design, build, and deploy agentic AI systems using frameworks such as LangChain, Lang Graph, and related libraries.&nbsp;&nbsp;</li><li>Develop and deploy multi-agent systems capable of autonomous decision-making, reasoning, planning, and collaboration.&nbsp;</li></ul> RAG Pipelines:&nbsp; <ul><li>Implement and optimize retrieval-augmented generation (RAG) systems, ensuring agents can access and incorporate external knowledge sources for grounded, accurate responses.&nbsp;</li></ul> LLM Engineering:&nbsp; <ul><li>Fine-tune and prompt-engineer LLMs for task-specific reasoning, planning, and dynamic adaptation.&nbsp;</li><li>Work with LLM/SLM APIs, embeddings, and advanced generative AI techniques.&nbsp;</li></ul> Enterprise AI Platform:&nbsp; <ul><li>Lead the development of enterprise-grade AI platforms integrating LLMs, RAG, embeddings, and agentic AI protocols.&nbsp;</li><li>Implement and standardize Model Context Protocol (MCP) for consistent context management across models and agents.&nbsp;</li></ul> MLOps &amp; Observability:&nbsp; <ul><li>Establish and enforce best practices for MLOps, monitoring, and observability, ensuring scalable and maintainable AI solutions.&nbsp;</li><li>Applied AI Prototyping:&nbsp;</li></ul> Rapidly prototype, experiment, and iterate to improve AI agent capabilities.&nbsp; Collaboration &amp; Research:&nbsp; <ul><li>Participate in the full research cycle: literature review, data exploration, experimentation, and presentation of findings.&nbsp;</li><li>Collaborate effectively with other engineers, researchers, and data scientists.&nbsp;</li><li>Contribute to the documentation and standardization of technical code and practices.&nbsp;</li></ul>&nbsp;Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related quantitative field. Master’s or Ph.D. is a strong plus.&nbsp;</li><li>5+ years overall experience in software development, data science, or machine learning.&nbsp;</li><li>1+ year of hands-on experience developing AI applications with LLMs and systems such as retrieval-based methods, fine-tuning, or agent-based architectures.&nbsp;</li><li>1+ year of experience with frameworks like LangChain, LlamaIndex, OpenAI, or similar tools.&nbsp;</li></ul>

Role Desscription: <ul><li>The key account and e-commerce manager is responsible for driving the execution of brand and commercial strategies across digital sales channels, ensuring excellence in online presence, promotion and conversion.</li><li>This role acts as the key interface between marketing, sales and eRetailers, translating brand &amp; commercial objectives into shopper-centric initiatives that enhance visibility, engagement, and sell out performance in the digital environment.</li></ul> Responsibilities: <ul><li>Connecting with distributors to drive sales in pure e-commerce players (Lazada, Shopee etc).</li><li>Ensure excellence in execution in e-commerce across pure players and also retail e-commerces.</li><li>Omnichannel execution. Ensure 360 activation of IMC in e-commerce platforms across focus markets in SSEA.</li></ul> Key Accountabilities <ul><li>Digital Channel Strategy Execution: translate brand and sales strategies into tailored online plans for each digital customer (marketplaces, B&amp;C, quick commerce). Align and execute commercial calendars, launches, and campaigns in collaboration with Sales and Marketing teams.</li><li>% of planned activities executed according to the digital commercial calendar.</li><li>Internal alignment score with Sales and Marketing (e.g., internal NPS or feedback in JBP sessions).</li><li>Number of campaigns successfully launched by channel/platform.</li></ul> <ul><li>Visibility and Conversion: Ensure best-in-class product content, imagery, and search optimization across all eRetail platforms.</li><li>Deploy digital trade initiatives (e.g., banners, activations, product sampling) to increase brand visibility and conversion.</li><li>Share of Search (SoS) for top keywords per platform.</li><li>Conversion Rate (CVR) by priority product and platform.</li><li>% of planned digital assets (e.g., banners, feature slots) executed on time.</li></ul> <ul><li>Promo &amp; Investment Planning: Coordinate digital promotional mechanics in line with budget, ROI, and brand guidelines.</li><li>Monitor competitive pricing and promotions to adjust plans accordingly.</li><li>ROI of promotional campaigns (% return on investment).</li><li>Budget adherence rate (% of trade digital budget spent as planned).</li><li>Sell-out growth during promotional periods (vs. pre-promo baseline or LY).</li></ul> <ul><li>Performance Analysis &amp; Reporting:</li><li>Track and analyze key performance indicators (e.g., sell-out, share of shelf, conversion rates, media ROI).</li><li>Generate actionable insights to optimize future campaigns and investments.</li><li>Accuracy of reported data (target: &lt;5% margin of error).</li></ul> <ul><li>Content &amp; Assortment Management:</li><li>Maintain accurate and complete product information, ensuring consistent presence across platforms.</li><li>Support in defining digital assortment priorities and product visibility strategies by platform.</li><li>% of SKUs with compliant, high-quality content live on each platform.</li><li>Time to market for new product content.</li><li>Assortment compliance rate per retailer (e.g., % of priority SKUs listed).</li></ul> Requirements: <ul><li>Experience Capability.</li><li>Graduation Complete.</li><li>MBA (Differential).</li></ul> Language <ul><li>Advanced English</li></ul> Discipline of Knowledge. <ul><li>Administration, Economics, Marketing</li></ul> Specific knowledge of the team you lead. <ul><li>Previous experience in FMCG Industries in E-commerce or in pure e-commerce players.</li><li>Proficiency in Excel and Power Point.</li><li>Project management.</li><li>Knowledge of Tableau (BI and Dashboards) or programming language.</li></ul> Organization <ul><li>Analytical – Working with data Management.</li></ul> Communication <ul><li>Teamwork.</li><li>Resilience and self-motivation.</li><li>Logical reasoning.</li><li>Ability to prioritize and sense of urgency.</li><li>Ability to execute.</li></ul>

Responsibilities: <ul><li>Oversee the design, development, and deployment of AI models and intelligent agents.</li><li>Ensure engineering best practices in model development, testing, and deployment.</li><li>Collaborate with IT and data teams to ensure scalable and secure integration of AI solutions.</li><li>Work closely with business and technical stakeholders to understand requirements and deliver impactful AI solutions.</li><li>Communicate effectively with global teams, bridging technical and business perspectives.</li><li>Support change management and adoption of AI tools across business units.</li><li>Stay current with advancements in AI and apply them to solve business challenges.</li><li>Participate in efforts to improve enterprise adoption and proficiency in the use of AI tools.</li><li>Lead the design and development of solutions using Agentic AI&nbsp;</li></ul> Requirements: Basic Qualifications:<ul><li>10+ years of experience in software engineering, data science, AI, or a related field.</li><li>2+ years of experience in leadership role managing technical teams.</li><li>Proficiency in software development and statistical analysis.</li><li>Experience with Large Language Models and their applications.</li><li>Strong communication skills and the ability to present technical results to business stakeholders.</li><li>Experience with solution architecting and design.</li><li>Hands-on experience with cloud platforms such as Azure and/or AWS. </li><li>Proficiency in programming languages such as Python, R, or similar.</li><li>Bachelor’s or master’s in computer science, Mathematics, Statistics, or a related field.</li></ul> Preferred Qualifications:<ul><li>Experience working in a global enterprise or matrixed organization.</li><li>Familiarity with cloud platforms (Azure, AWS, GCP) and MLOps tools.</li><li>Experience with large language models and supporting workflows.</li><li>History of project leadership and development.</li><li>Experience in applications to sales, marketing, and market research&nbsp;</li></ul>

Responsibilities: <ul><li>Together with the team of developers handle the product quality.</li><li>Lead and manage the automation testing efforts and deliverables.</li><li>Plan and prioritize testing activities.</li><li>Maintain and improve an existing test automation framework.</li><li>Develop automation tests for API and UI.</li><li>Execute, maintain and update automation tests.</li><li>Review and analyze tests execution results.</li><li>Maintain all related test documentation.</li><li>Prepare testing data.</li><li>Proactively acquire and clarify requirements as necessary.</li><li>Mentor less skilled teammates and newcomers.</li></ul> Requirements: <ul><li>Strong knowledge of OOP (understanding OOP in automation).</li><li>Excellent knowledge of automation testing principles.</li><li>Excellent knowledge of web-based application structure.</li><li>Excellent knowledge of Python programming language.</li><li>Expert in REST API testing.</li><li>Experience in UI testing.</li><li>Wide experience in developing automation testing frameworks.</li></ul>

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56 python programming Jobs found

C# Developer (SSE)

Docusign Developer

Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Solution Engineer - Security

IIAD / SAD / LAD Artificial Intelligence Engineer

Key Account and E-Commerce Manager

Lead AI Engineer

Senior QA Automation Engineer

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56 python programming Jobs found

C# Developer (SSE)

Docusign Developer

Solution Engineer - AI Infrastructure

Senior Machine Learning Engineer (Production & MLOps Focus)

Data & Business Intelligence Analyst

Solution Engineer - Security

IIAD / SAD / LAD Artificial Intelligence Engineer

Key Account and E-Commerce Manager

Lead AI Engineer

Senior QA Automation Engineer

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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WhiteCrow
WhiteCrow is on a mission to connect companies with the best talent across the globe.