<p>Senior Developer - AI/ML & Generative AI (Airflow, Python, MLOps)</p> <p>Location: Hybrid (Chicago, IL)</p> <p>Experience: 6-10+ years</p> <p>About Cognizant</p> <p>Cognizant is a leading global professional services company, helping organizations modernize technology, reimagine processes, and transform customer experiences. We leverage expertise in AI, cloud, and digital engineering to deliver measurable outcomes across industries.</p> <p>Role Overview</p> <p>We are seeking a Senior Developer with strong expertise in data engineering, AI/ML, and Generative AI to build scalable, production-grade solutions.</p> <p>This role focuses on developing Airflow-orchestrated pipelines, operationalizing machine learning models, and building reusable AI frameworks that drive smarter business decisions and deliver meaningful impact.</p> <p>Key Responsibilities</p> <p>Data Pipelines & Workflow Orchestration</p> <ul> <li>Design and implement robust data and model pipelines using Apache Airflow </li><li>Orchestrate complex workflows ensuring reliability, scalability, and performance across hybrid environments </li></ul> <p>AI & Generative AI Development</p> <ul> <li>Develop Generative AI services to transform enterprise data into insights and content </li><li>Ensure solutions meet accuracy, safety, and compliance standards </li><li>Apply prompt engineering and model integration techniques in business applications </li></ul> <p>ML Engineering & Productionization</p> <ul> <li>Build production-ready machine learning solutions from experimental prototypes </li><li>Develop scalable services with monitoring, logging, and fault tolerance </li><li>Ensure consistent delivery of value to downstream systems </li></ul> <p>MLOps & Automation</p> <ul> <li>Implement MLOps best practices, including automated training, evaluation, deployment, and rollback </li><li>Enhance development velocity through CI/CD automation and lifecycle management </li></ul> <p>Data Engineering & Feature Management</p> <ul> <li>Build and maintain feature pipelines and data preparation processes </li><li>Ensure high-quality, governed, and traceable data for model training and inference </li></ul> <p>Observability & Reliability</p> <ul> <li>Implement monitoring, logging, and alerting for pipelines and models </li><li>Detect and resolve issues related to data quality, model drift, and system performance </li></ul> <p>Collaboration & Delivery</p> <ul> <li>Partner with data scientists, engineers, and product stakeholders to translate ideas into scalable solutions </li><li>Contribute to backlog prioritization and iteration planning </li></ul> <p>Standards, Governance & Best Practices</p> <ul> <li>Ensure security, privacy, and responsible AI principles are embedded in solutions </li><li>Promote best practices in version control, testing, and CI/CD </li></ul> <p>Innovation & Continuous Improvement</p> <ul> <li>Evaluate emerging tools in Generative AI and MLOps </li><li>Support experimentation through A/B testing and model comparison frameworks </li></ul> <p>Mentorship & Leadership</p> <ul> <li>Mentor junior developers on Airflow, debugging, and deployment strategies </li><li>Foster a collaborative and growth-oriented team environment </li></ul> <p>Required Qualifications</p> <ul> <li>Strong experience in Python-based development for data and AI applications </li><li>Hands-on expertise with Apache Airflow (DAG design, operators, scheduling optimization) </li><li>Solid understanding of machine learning concepts (supervised/unsupervised learning, evaluation, feature engineering) </li><li>Practical experience with MLOps practices (packaging, deployment, monitoring, lifecycle management) </li><li>Experience implementing Generative AI solutions (prompt design, model integration) </li><li>Strong SQL and data modeling skills for high-performance data pipelines </li></ul> <p>Preferred Qualifications</p> <ul> <li>Experience with containerization (Docker, Kubernetes) </li><li>Exposure to cloud platforms (AWS, Azure, or GCP) </li><li>Familiarity with CI/CD pipelines and DevOps practices </li><li>Knowledge of Responsible AI frameworks and governance models </li><li>Experience working in enterprise-scale, hybrid environments </li><li>Strong communication and stakeholder management skills </li></ul> <p>Certifications (Preferred)</p> <ul> <li>TensorFlow Developer Certification </li><li>AWS Certified Machine Learning - Specialty </li><li>Equivalent certifications in AI/ML or MLOps </li></ul> <p>Compensation</p> <ul> <li>Base Salary Range: $120,000 - $130,000 per year </li><li>Final compensation is based on experience, skills, and location </li><li>Eligible for performance-based bonuses and incentive compensation </li></ul> <p>Benefits</p> <p>Cognizant offers a comprehensive benefits package to support your well-being and career growth:</p> <ul> <li>Health & Wellness: Medical, dental, and vision insurance </li><li>Financial Benefits: 401(k) with company match, life and disability insurance </li><li>Time Off: Generous PTO, paid holidays, and parental leave </li><li>Learning & Development: Access to certifications, training programs, and career advancement opportunities </li><li>Flexible Work: Hybrid work model to support work-life balance </li><li>Employee Experience: Wellness programs, employee resource groups, and recognition initiatives </li></ul> <p>Why Join Cognizant?</p> <ul> <li>Work on cutting-edge Generative AI and ML solutions </li><li>Collaborate with global clients and cross-functional teams </li><li>Grow your career in a high-demand, innovation-driven space </li><li>Be part of a company committed to inclusion, diversity, and impact </li></ul>