Graphic Designer

📍 Job Overview

Job Title: Graphic Designer

Company: Weekday AI (Client Role)

Location: Bengaluru, Karnataka, India

Job Type: Full-time

Category: Operations Technology & Software Engineering

Date Posted: 2026-07-29

Experience Level: Mid-Level (3+ years)

Remote Status: On-site

🚀 Role Summary

• This role is for a client of Weekday AI, focusing on building next-generation, AI-powered enterprise software.

• It involves designing, developing, and maintaining scalable, high-quality software solutions that leverage intelligent automation and real-time insights.

• The position requires collaboration with product managers, designers, and engineering teams to deliver innovative product features.

• Key responsibilities include optimizing applications for automation, data-driven decision-making, and contributing to system design and architecture discussions.

• The role emphasizes writing clean, efficient, and well-tested code, troubleshooting technical issues, and adhering to security, scalability, and performance best practices.

📝 Enhancement Note: While the job title is "Graphic Designer," the provided description and responsibilities clearly indicate a Software Engineer or Product Engineer role, with a strong emphasis on AI-powered enterprise software development, automation, and data-driven insights. The "Graphic Designer" title appears to be a misclassification. This enhancement will proceed with the assumption that the role is for a Software Engineer focused on operations technology.

📈 Primary Responsibilities

• Design, develop, and maintain scalable, high-quality software solutions that align with business and customer requirements, ensuring robust and efficient enterprise software.

• Collaborate closely with product managers, UX/UI designers, and cross-functional engineering teams to conceptualize, build, and deliver innovative product features that enhance operational efficiency.

• Build and optimize applications that effectively leverage AI-enabled capabilities, intelligent automation workflows, and real-time data-driven insights for improved business outcomes.

• Actively participate in system design and architecture discussions, contributing to technical decision-making for scalable, maintainable, and secure solutions within the operations technology stack.

• Write clean, efficient, well-tested, and maintainable code, adhering strictly to established engineering best practices, coding standards, and object-oriented programming principles.

• Troubleshoot, debug, and resolve complex technical issues across the software lifecycle, continuously identifying opportunities to improve application performance, reliability, and user experience.

• Contribute to a culture of continuous improvement through active participation in code reviews, technical documentation, and knowledge-sharing initiatives within the engineering team.

• Work in close partnership with QA and DevOps teams to support comprehensive testing, seamless deployment, and the implementation of continuous integration and continuous delivery (CI/CD) processes.

• Stay abreast of emerging technologies, particularly in AI, automation, and cloud computing, and proactively recommend improvements to enhance product capabilities and overall engineering efficiency.

• Ensure strict adherence to security, scalability, and performance best practices throughout the entire software development lifecycle, safeguarding data integrity and system robustness.

📝 Enhancement Note: The core responsibilities have been expanded to reflect common duties of a Software Engineer in an AI-focused enterprise software company, emphasizing aspects relevant to operations technology, automation, and data-driven solutions. The original description was concise, and this expansion provides more detail on the scope and impact of the role within an operations context.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent practical experience.

Experience: 3+ years of professional experience in software development, product engineering, or a related technical role within the enterprise software or AI technology sectors.

Required Skills:

• Strong proficiency in modern programming languages (e.g., Python, Java, Go, C++) and associated software development frameworks.

• Proven experience in cloud-native application development, utilizing microservices, containers, and serverless architectures.

• Demonstrated experience building scalable enterprise applications using distributed systems and robust API-driven architectures.

• Good understanding of AI-enabled applications, machine learning concepts, automation workflows, or data-driven software solutions.

• Familiarity with cloud platforms (AWS, Azure, GCP), relational and NoSQL databases, version control systems (e.g., Git), and CI/CD practices.

• Strong knowledge of software design principles, object-oriented programming (OOP), and performance optimization techniques.

• Excellent analytical, debugging, and problem-solving skills with a methodical approach to issue resolution.

• Strong communication and collaboration abilities, with a proven track record of working effectively in cross-functional product teams.

• Self-driven mindset with the ability to take ownership of features from initial design through to final deployment and maintenance.

• Demonstrated passion for innovation, continuous learning, and building impactful technology solutions that address real-world business challenges. Preferred Skills:

• Experience with specific AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

• Familiarity with business process management (BPM) tools or workflow automation platforms.

• Knowledge of data pipeline construction and data warehousing concepts.

• Experience with container orchestration platforms like Kubernetes.

• Familiarity with agile development methodologies (Scrum, Kanban).

• Understanding of enterprise security best practices and compliance standards.

📝 Enhancement Note: The qualifications have been structured to align with a mid-level Software Engineer role. Specific programming languages and cloud platforms have been added as examples to provide clarity. Preferred skills have been included to highlight desirable, but not mandatory, proficiencies that would benefit an operations technology focus.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase at least 2-3 significant software development projects or contributions that demonstrate your ability to build scalable, reliable, and efficient enterprise solutions.

• Highlight projects that involve AI-enabled features, automation workflows, or data-driven insights, clearly articulating the problem, your solution, and the impact.

• Include examples of system design or architecture contributions, illustrating your approach to building robust and maintainable systems.

• Demonstrate proficiency in code quality, including examples of well-structured, tested, and documented code.

• Provide evidence of experience with CI/CD pipelines, version control, and collaborative development workflows. Process Documentation:

• Candidates are expected to articulate their understanding and experience with software development lifecycle (SDLC) methodologies, including agile practices.

• Be prepared to discuss your approach to system design, architecture planning, and technical decision-making processes.

• Demonstrate an understanding of debugging and troubleshooting methodologies, including root cause analysis.

• Expected to discuss experience with code review processes and their importance in ensuring code quality and knowledge sharing.

📝 Enhancement Note: Given the technical nature of the role, a portfolio is crucial. This section outlines what a strong portfolio for a software engineer focused on operations technology might include, emphasizing process documentation and system design aspects relevant to building AI-powered enterprise software.

💵 Compensation & Benefits

Salary Range: INR 5,00,000 - INR 14,00,000 LPA (Lakhs Per Annum)

Benefits:

• Competitive salary package commensurate with experience and qualifications.

• Opportunity to work with cutting-edge AI and enterprise software technologies.

• Exposure to a fast-paced product engineering environment with continuous innovation.

• Collaborative and dynamic team culture focused on growth and learning.

• Health insurance and wellness programs.

• Paid time off and holidays.

• Professional development opportunities, including training and workshops.

Working Hours: Standard full-time engagement, likely around 40 hours per week, with flexibility expected to meet project deadlines and operational needs.

📝 Enhancement Note: The salary range provided in the input data has been formatted and clarified. Benefits have been inferred based on standard offerings for full-time tech roles in India, with a focus on aspects appealing to software engineers in an innovative environment. The working hours are based on the ai_working_hours field.

🎯 Team & Company Context

🏢 Company Culture

Industry: Artificial Intelligence (AI), Enterprise Software, Technology Solutions.

Company Size: The description implies a growing, agile team within a larger client organization, likely a mid-sized to large enterprise focused on AI transformation.

Founded: The company context is that of a client of Weekday AI, suggesting an established entity seeking specialized talent for advanced AI projects. The founding date is not specified, but the focus on "next-generation" software implies a forward-thinking organization.

Team Structure:

• The operations technology team is likely structured around product development, with engineers collaborating closely with product managers and designers.

• Reporting structure will probably involve a Tech Lead or Engineering Manager overseeing a pod or squad focused on specific features or product areas.

• Cross-functional collaboration is a core tenet, with regular interaction between engineering, product, design, QA, and DevOps teams. Methodology:

• Data analysis and insights are central to the product's value proposition, informing development priorities and feature enhancements.

• Workflow planning and optimization strategies are critical for building efficient automation.

• Automation and efficiency practices are core to the company's mission of transforming business operations.

Company Website: [Weekday AI Client Website - To be provided by candidate or recruiter]

📝 Enhancement Note: This section infers the company culture and structure based on the description of building "next-generation, AI-powered enterprise software" and operating in a "fast-paced product engineering environment." The "client role" aspect is noted as a key differentiator.

📈 Career & Growth Analysis

Operations Career Level: This role represents a Mid-Level Software Engineer position. It requires independent contribution to feature development, system design input, and problem-solving, moving beyond junior-level task execution. The focus on AI and enterprise software suggests opportunities to specialize in advanced technology domains.

Reporting Structure: The engineer will likely report to a Senior Engineer, Tech Lead, or Engineering Manager. They will be part of a development team that collaborates extensively with Product Management and Design.

Operations Impact: The role has a direct impact on the functionality and efficiency of enterprise software solutions. By developing AI-powered features and automation, the engineer contributes to enhancing operational workflows, improving data-driven decision-making, and ultimately driving business growth and customer satisfaction for the client.

Growth Opportunities:

• Operations Skill Advancement: Opportunities to deepen expertise in AI/ML, cloud-native architectures, distributed systems, and automation technologies.

• Leadership Potential: Progression to Senior Engineer, Tech Lead, or Architect roles, involving more complex design, mentoring junior engineers, and driving technical strategy.

• Specialization: Potential to specialize in areas such as AI/ML engineering, backend systems, cloud infrastructure, or performance optimization within the operations technology domain.

• Cross-functional Exposure: Gain experience working across different product lines or modules within the enterprise software suite.

📝 Enhancement Note: This analysis focuses on the career trajectory and impact typical for a mid-level software engineer in a company prioritizing AI and operational efficiency, aligning with the "operations technology" interpretation of the role.

🌐 Work Environment

Office Type: On-site role in Bengaluru, indicating a traditional office environment conducive to in-person collaboration and structured work.

Workspace Context:

• The environment is described as a "fast-paced product engineering environment," suggesting a dynamic and potentially demanding workplace.

• Expect access to modern development tools, hardware, and collaborative spaces designed to foster innovation and teamwork.

• Opportunities for regular interaction with a diverse team of engineers, product managers, and designers, facilitating knowledge exchange and collaborative problem-solving.

Work Schedule: Full-time, on-site in Bengaluru. While standard hours are expected, the fast-paced nature implies potential for flexible scheduling or occasional extended hours to meet project milestones.

📝 Enhancement Note: Based on the "On-site" and "Bengaluru" location, this section details the expected physical and collaborative aspects of the work environment for a software engineering role.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will assess your resume and experience, focusing on your 3+ years of software development, AI/automation exposure, and cloud experience.

• Technical Assessment: Expect a coding challenge or technical interview focusing on data structures, algorithms, object-oriented programming, and problem-solving skills, potentially using a platform like HackerRank or CoderPad.

• System Design Interview: A discussion on designing scalable, AI-driven systems, troubleshooting scenarios, and architectural choices relevant to enterprise software.

• Cross-functional/Behavioral Interview: Discussion with product managers or senior engineers to assess collaboration, communication, problem-solving approach, and cultural fit within the team.

• Final Interview: May involve a senior leader to discuss overall fit, career aspirations, and alignment with company vision.

Portfolio Review Tips:

• Curate Select Projects: Choose 2-3 projects that best showcase your most relevant skills: AI/automation, scalability, enterprise software development, and strong coding practices.

• Structure Your Case Studies: For each project, clearly outline the problem statement, your role and contributions, the technologies used, the technical challenges overcome, and the quantifiable impact or outcome.

• Highlight Operations Relevance: Emphasize how your projects contributed to efficiency, automation, data-driven decision-making, or improved operational workflows.

• Prepare for Code Walkthroughs: Be ready to discuss your code architecture, design decisions, and coding standards in detail.

• Showcase Problem-Solving: Be prepared to articulate complex problems you've solved and your systematic approach to finding solutions.

Challenge Preparation:

• Coding Practice: Focus on LeetCode-style problems (Easy/Medium) covering arrays, strings, trees, graphs, and dynamic programming. Practice coding in your primary language.

• System Design Fundamentals: Review common system design patterns, scalability concepts, database choices, and API design principles. Consider how to design for AI integration.

• AI/Automation Concepts: Brush up on basic AI/ML concepts and how they are applied in enterprise software. Understand common automation workflow patterns.

• Behavioral Questions: Prepare STAR method (Situation, Task, Action, Result) answers for common behavioral questions related to teamwork, problem-solving, and handling challenges.

📝 Enhancement Note: This section provides a detailed breakdown of the likely interview process and preparation strategies for a mid-level software engineer role, with a specific focus on the AI and operations technology aspects.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python, Java, Go, C++ (or similar modern languages).

• Cloud Platforms: AWS, Azure, or GCP.

• Version Control: Git (e.g., GitHub, GitLab, Bitbucket).

• Databases: SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases.

• Containers & Orchestration: Docker, Kubernetes.

Analytics & Reporting:

• Tools for monitoring application performance and health (e.g., Prometheus, Grafana, Datadog).

• Logging and analysis tools (e.g., ELK Stack, Splunk).

• Potentially business intelligence tools for understanding user adoption and feature impact. CRM & Automation:

• While not directly a CRM role, understanding how enterprise software integrates with CRM systems (e.g., Salesforce, HubSpot) may be beneficial.

• Workflow automation tools or frameworks relevant to building intelligent automation.

• API Gateway technologies for managing service integrations.

📝 Enhancement Note: This list of tools and technologies is inferred based on the job description's emphasis on cloud-native development, AI, distributed systems, and enterprise software.

👥 Team Culture & Values

Operations Values:

• Innovation: A strong drive to explore and implement new technologies, particularly in AI and automation, to push the boundaries of enterprise software.

• Excellence & Quality: Commitment to delivering high-quality, reliable, and scalable software solutions, with a focus on clean code and robust engineering practices.

• Collaboration & Teamwork: Emphasis on working effectively within cross-functional teams, sharing knowledge, and supporting colleagues to achieve common goals.

• Data-Driven Approach: Utilizing data and insights to inform product development, feature prioritization, and continuous improvement of operational efficiency.

• Customer Focus: Dedication to building solutions that solve real-world business challenges and deliver significant value to customers.

Collaboration Style:

• Cross-functional Integration: Engineers are expected to actively collaborate with Product Managers, Designers, QA, and DevOps, fostering a holistic approach to product development.

• Agile & Iterative: Embracing agile methodologies for iterative development, continuous feedback, and rapid adaptation to changing requirements.

• Knowledge Sharing: A culture that encourages open communication, code reviews, and sharing of technical expertise to elevate the entire team's capabilities.

📝 Enhancement Note: These values and collaboration styles are inferred from the description of a "fast-paced product engineering environment" focused on "AI-powered enterprise software" and "intelligent automation."

⚡ Challenges & Growth Opportunities

Challenges:

• Rapid Technological Evolution: Keeping pace with the fast-evolving landscape of AI, cloud computing, and software development best practices.

• Scalability & Performance: Ensuring solutions remain performant and scalable as user bases and data volumes grow significantly.

• Complexity of AI Integration: Effectively integrating complex AI models and automation into robust enterprise software workflows requires careful design and implementation.

• Balancing Innovation with Stability: Driving innovation while maintaining the stability, security, and reliability expected of enterprise-grade software.

Learning & Development Opportunities:

• Specialized Training: Access to training programs and resources focused on AI/ML, cloud architecture, distributed systems, and specific development tools.

• Industry Conferences: Opportunities to attend relevant tech conferences and workshops to stay updated on industry trends and network with peers.

• Mentorship: Potential to learn from senior engineers and architects, gaining insights into advanced design patterns and strategic technical decision-making.

• Project Variety: Exposure to diverse projects and challenges within the enterprise software domain, allowing for broad skill development.

📝 Enhancement Note: This section identifies potential challenges and growth avenues inherent in a role focused on cutting-edge AI and enterprise software development.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex software system you designed or significantly contributed to. What were the key architectural decisions and trade-offs? How did you ensure scalability and performance?" (Focus on demonstrating system design skills and understanding of operations technology principles.)

• "Walk me through a challenging bug you encountered. What was your systematic approach to debugging, and how did you prevent similar issues in the future?" (Highlight problem-solving methodology and attention to detail.)

• "How would you approach building an AI-powered feature that automates a common business process? What data considerations would be critical?" (Assess understanding of AI application in operations and data requirements.)

• "Describe a time you had to collaborate with non-technical stakeholders (e.g., product managers, designers) on a technical project. How did you ensure clear communication and alignment?" (Evaluate communication and cross-functional collaboration skills.) Company & Culture Questions:

• "Why are you interested in working for a client of Weekday AI, specifically in the AI-powered enterprise software space?" (Research Weekday AI's focus and the client's industry if possible.)

• "What are your thoughts on the future of AI in transforming business operations?" (Demonstrate passion and forward-thinking perspective.)

• "How do you stay updated with the latest advancements in software development and AI?" (Showcase continuous learning mindset.) Portfolio Presentation Strategy:

• Impact-Oriented Storytelling: For each project, focus on the "why" and the "what was achieved." Start with the business problem or operational challenge.

• Quantify Results: Use metrics whenever possible to demonstrate the impact of your work (e.g., "reduced processing time by X%", "improved accuracy by Y%", "handled Z% more requests").

• Technical Depth: Be ready to dive deep into the technical implementation, architecture, and specific coding challenges, but tailor the level of detail to your audience.

• Process Clarity: Clearly articulate the development process followed, including design, testing, and deployment phases, especially any involvement with CI/CD.

• Showcase AI/Automation: If applicable, clearly explain how AI or automation was implemented and the benefits it delivered to the business operations.

📝 Enhancement Note: These interview questions and preparation tips are tailored to a mid-level Software Engineer role focused on AI and enterprise operations technology, emphasizing technical skills, problem-solving, and understanding of business impact.

📌 Application Steps

To apply for this operations technology position:

• Submit your application through the provided Workable portal link.

• Resume Optimization: Tailor your resume to highlight your 3+ years of software development experience, specific accomplishments in AI-enabled applications, automation workflows, distributed systems, and cloud technologies. Use keywords from the job description.

• Portfolio Preparation: Select 2-3 of your strongest software development projects that best showcase your skills in building scalable enterprise solutions. Prepare to articulate the problem, your solutions, the technologies used, and the measurable impact, with a focus on operational efficiency and AI integration.

• Technical Skill Refinement: Brush up on core programming concepts, data structures, algorithms, and system design principles. Practice coding exercises and review common AI/automation concepts relevant to enterprise software.

• Company Research: Understand Weekday AI's role as a talent provider and research the client's industry and focus area (AI-powered enterprise software) to articulate your interest effectively during interviews.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. The role title "Graphic Designer" is likely a misclassification, and the content has been tailored for a Software Engineer role focused on AI-powered enterprise software and operations technology. All details should be verified directly with the hiring organization before making application decisions.