Job Title

HCLTech is hiring Data and AI Principal /Senior Manager (Generative AI) for Noida. HCLTech is a global technology company, home to more than 218,000 people across 59 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. Consolidated revenues as of 12 months ending September 2024 totaled $13.7 billion. To learn how we can supercharge progress for you, visit . Key Responsibilities: Hands-on Technical Leadership & Oversight: Architecting Scalable Systems : Lead the design of AI, GenAI solutions , machine learning pipelines , and data architectures that ensure performance , scalability , and resilience . Hands-on Development : Actively contribute to coding , code reviews , solution design , and hands-on troubleshooting for critical components of GenAI , ML , and data pipelines . Cross-Functional Collaboration : Work with Account Teams , Client Partners and Domain SMEs to ensure alignment between technical solutions and business needs. Team Leadership : Mentor and guide engineers across various functions including AI, GenAI , Full Stack, Data Pipelines , DevOps , and Machine Learning , fostering a collaborative and high-performance team environment. Solution Design & Architecture: System & API Architecture : Design and implement microservices architectures , RESTful APIs , cloud-based services , and machine learning models that integrate seamlessly into GenAI and data platforms . AI, GenAI, Agentic AI Integration : Lead the integration of AI, GenAI, and Agentic applications , NLP models , and large language models ( e.g., GPT , BERT ) into scalable production systems. Data Pipelines : Architect ETL pipelines , data lakes , and data warehouses using industry-leading tools like Apache Spark , Airflow , and Google BigQuery . Cloud Infrastructure : Drive the deployment and scaling of solutions using cloud platforms like AWS , Azure , GCP , and other relevant cloud-native technologies. Machine Learning & AI Solutions: ML Integration : Lead the design and deployment of machine learning models using frameworks like PyTorch , TensorFlow , scikit-learn , and spaCy into end-to-end production workflows, including building of SLMs. Prompt Engineering : Develop and optimize prompt engineering techniques for GenAI models to ensure accurate, relevant, and reliable output. Model Monitoring : Implement best practices for ML model performance monitoring , continuous training, and model versioning in production environments. DevOps & Cloud Infrastructure: CI/CD Pipeline Leadership : Have good working knowledge of CI/CD pipelines , leveraging tools like Jenkins , GitLab CI , Terraform , and Ansible for automating the build, test, and deployment processes. Infrastructure Automation : Lead efforts in Infrastructure-as-Code and ensure automated provisioning of infrastructure through tools like Terraform , CloudFormation , Docker , and Kubernetes . Cloud Management : Ensure robust integration with cloud platforms such as AWS , Azure , GCP , and experience with specific services such as AWS Lambda , Azure ML , Google BigQuery , and others. Cross-Team Collaboration: Stakeholder Communication : Act as the key technical liaison between engineering teams and non-technical stakeholders, ensuring technical solutions meet business and user requirements. Agile Development : Promote Agile methodologies and do solution and code design reviews to deliver milestones efficiently while ensuring high-quality code. Performance Optimization & Scalability: Optimization : Lead performance tuning and optimization for high-traffic applications, especially around machine learning models , data storage , ETL processes , and API latency . Scaling : Ensure solutions scale seamlessly with growth, leveraging cloud-native tools and load balancing strategies such as AWS Auto Scaling , Azure Load Balancer , Kubernetes Horizontal Pod Autoscaler . Required Qualifications: 15+ years of hands-on technical experience in software engineering, with at least 5+ years in a leadership role managing cross-functional teams, including AI, GenAI , machine learning , data engineering , and cloud infrastructure . Hands-on Experience in designing and developing large-scale systems , including AI, GenAI , Agentic AI, API architectures , data systems , ML pipelines , and cloud-native applications . Strong experience with cloud platforms such as AWS , GCP , Azure with a focus on cloud services related to ML , AI , and data engineering . Programming Languages : Proficiency in Python , Flask/Django/FastAPI Experience with API development (RESTful APIs, GraphQL ). Machine Learning & AI : Extensive experience in building and deploying ML models using TensorFlow , PyTorch , scikit-learn , and spaCy , with hands-on experience in integrating them into AI, GenAI and Agentic frameworks like LangChain and MCP . Data Engineering : Familiarity with ETL pipelines , data lakes , data warehouses (e.g., AWS Redshift , Google BigQuery , PostgreSQL ), and data processing tools like Apache Spark , Airflow , and Kafka . DevOps & Automation : Strong expertise in CI/CD pipelines, containerization (Docker , Kubernetes ), Infrastructure-as-Code (Terraform , CloudFormation , Ansible ). Experience with API security , OAuth , and rate limiting for high-traffic, secure systems. Tools & Technologies: Cloud Platforms : AWS, GCP, Azure, Google Cloud AI, AWS SageMaker, Azure Machine Learning. Data Engineering : A pache Kafka, Apache Spark, Airflow, Presto, Hadoop, Google BigQuery, AWS Redshift. Machine Learning : TensorFlow, PyTorch, scikit-learn, spaCy, HuggingFace, OpenAI GPT. CI/CD & DevOps : GitLab CI, Jenkins, Docker, Kubernetes, Terraform, Ansible, Helm. API Frameworks : FastAPI, Flask, GraphQL, RESTful APIs. Version Control : Git, GitHub, GitLab. Interested candidates, kindly share your profile on with below details. Overall Experience: Skills: Current and Preferred Location: Current and Expected CTC: Notice Period: