Keywords to Search : AI/ML,LLM, Deep learning.
No. of Openings 4
Experience 4 To 6 Year(s)
Skill set Generative AI, LLM, RAG, Model Fine-tuning, Deep-Learning, Transformers (Please interview internally and Upload only pre-vetted profiles)
Domain knowledge Experience:
o Proven experience in developing and working with state-of-the-art large language models (LLMs) such as GPT, BERT, T5, or other transformer-based models.
o Strong expertise in training, fine-tuning, and optimizing LLMs for real-world applications.
o Hands-on experience with ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers, etc.
o Experience with advanced techniques in NLP such as attention mechanisms, transfer learning, and few-shot learning.
o Practical knowledge of deploying AI models at scale in production environments.
• Skills:
o Expertise in deep learning and machine learning algorithms, particularly in the context of generative models.
o Proficiency in programming languages like Python, and familiarity with libraries such as NumPy, Pandas, Scikit-learn, and others.
o Familiarity with cloud-based solutions and tools (AWS, GCP, or Azure) for scalable model training and deployment.
o Knowledge of distributed computing and parallelism for large-scale training.
Job Description As a Generative AI Engineer specialized in Large Language Models (LLMs), you will work on developing, implementing, and optimizing state-of-the-art generative models that tackle a wide range of complex challenges in AI. You will be part of a multidisciplinary team pushing the frontiers of language understanding and generation, contributing to the research, development, and deployment of large-scale AI systems that can generate coherent, contextually aware, and human-like text.
Key Responsibilities:
• Research & Development: Lead and contribute to research initiatives focused on generative models, particularly LLMs like GPT, BERT, T5, and cutting-edge transformer architectures.
• Model Design & Implementation: Design, implement, and optimize LLM architectures for text generation, completion, summarization, and other NLP tasks.
• Training & Fine-Tuning: Conduct training and fine-tuning of large-scale models on specialized datasets, leveraging modern machine learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Optimization: Work on scaling, optimizing, and improving the efficiency of large models, including distributed training, parallelism, and hardware acceleration (GPUs, TPUs).
• Deployment & Integration: Collaborate with engineering teams to integrate generative models into production systems and applications, ensuring the scalability, robustness, and efficiency of deployed models.
Responsibilities
Keywords to Search : AI/ML,LLM, Deep learning.
No. of Openings 4
Experience 4 To 6 Year(s)
Skill set Generative AI, LLM, RAG, Model Fine-tuning, Deep-Learning, Transformers (Please interview internally and Upload only pre-vetted profiles)
Domain knowledge Experience:
o Proven experience in developing and working with state-of-the-art large language models (LLMs) such as GPT, BERT, T5, or other transformer-based models.
o Strong expertise in training, fine-tuning, and optimizing LLMs for real-world applications.
o Hands-on experience with ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers, etc.
o Experience with advanced techniques in NLP such as attention mechanisms, transfer learning, and few-shot learning.
o Practical knowledge of deploying AI models at scale in production environments.
• Skills:
o Expertise in deep learning and machine learning algorithms, particularly in the context of generative models.
o Proficiency in programming languages like Python, and familiarity with libraries such as NumPy, Pandas, Scikit-learn, and others.
o Familiarity with cloud-based solutions and tools (AWS, GCP, or Azure) for scalable model training and deployment.
o Knowledge of distributed computing and parallelism for large-scale training.
Job Description As a Generative AI Engineer specialized in Large Language Models (LLMs), you will work on developing, implementing, and optimizing state-of-the-art generative models that tackle a wide range of complex challenges in AI. You will be part of a multidisciplinary team pushing the frontiers of language understanding and generation, contributing to the research, development, and deployment of large-scale AI systems that can generate coherent, contextually aware, and human-like text.
Key Responsibilities:
• Research & Development: Lead and contribute to research initiatives focused on generative models, particularly LLMs like GPT, BERT, T5, and cutting-edge transformer architectures.
• Model Design & Implementation: Design, implement, and optimize LLM architectures for text generation, completion, summarization, and other NLP tasks.
• Training & Fine-Tuning: Conduct training and fine-tuning of large-scale models on specialized datasets, leveraging modern machine learning frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Optimization: Work on scaling, optimizing, and improving the efficiency of large models, including distributed training, parallelism, and hardware acceleration (GPUs, TPUs).
• Deployment & Integration: Collaborate with engineering teams to integrate generative models into production systems and applications, ensuring the scalability, robustness, and efficiency of deployed models.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Cyber Security Solution Architect:
Location: India (Preferred: Bangalore, Chennai, Pune)
As a Solution Architect in Cognizant’s Cyber Security Practice, you will design and deliver secure, scalable, and innovative solutions that align with client business objectives and industry best practices. This role combines deep technical expertise with strategic thinking to enable Cognizant’s growth in cybersecurity services, with a strong focus on leveraging Artificial Intelligence to solve complex security challenges.
Key Responsibilities
• Solution Design & Architecture
• Develop end-to-end cybersecurity architectures for enterprise, cloud, hybrid, and IoT environments.
• Translate client requirements into robust, compliant, and cost-effective security solutions.
• Lead architecture reviews for Zero Trust, Network Security, IAM, Data Protection, Threat & Vulnerability Management, and Cloud Security.
• Integrate and leverage AI for Cyber Security, utilizing platforms like Gemini, Microsoft Copilot, and Claude to enhance outputs and solution design.
• Work closely with technology vendors for collaboration on services offerings creation and reference architecture.
• Support RFP/RFI responses and create compelling solution narratives.
• Collaborate with sales and delivery teams to shape proposals and transformation roadmaps.
• Conduct workshops and create and deliver compelling presentations for clients on emerging security trends.
• Ensure solutions adhere to regulatory frameworks (NIST, ISO 27001, GDPR, HIPAA).
• Drive security risk assessments and compliance audits for proposed architectures.
• Stay ahead of industry trends such as Post-Quantum Cryptography, AI-driven security, SASE, and IoT Security.
• Evangelize Cognizant’s cybersecurity offerings and contribute to practice growth initiatives.
Required Skills & Expertise
• Technical Skills
• Strong knowledge of cybersecurity principles, Zero Trust, IAM, Data Security, Cloud Security, PKI, and cryptography.
• Expertise in AI for Cyber Security and familiarity with leveraging large language models (e.g., Gemini, Microsoft Copilot) for security use cases.
• Expertise in cloud security (AWS, Azure, GCP) and security architecture frameworks (SABSA, TOGAF).
• Knowledge of emerging areas like Post-Quantum Cryptography and IoT Security.
• Certifications
• Preferred: CISSP, CCSP, CISM, or equivalent.
• Recommended: Cloud security certifications (AWS/Azure/GCP Security Specialty).
• Soft Skills
• Excellent communication and stakeholder management.
• Proven capability to create high-quality presentations and present complex technical solutions effectively to both technical and non-technical client stakeholders.
• Ability to articulate complex technologies and security concepts in a clear, concise, and easy-to-understand manner.
• Ability to lead and co-ordinate with cross-functional teams and drive consensus.
• Analytical thinking and problem-solving under pressure.
Experience
• 12–18 years in cybersecurity with at least 5 years in solution architecture.
• Proven track record in designing enterprise security solutions and leading large-scale transformation programs.
Responsibilities
Cyber Security Solution Architect:
Location: India (Preferred: Bangalore, Chennai, Pune)
As a Solution Architect in Cognizant’s Cyber Security Practice, you will design and deliver secure, scalable, and innovative solutions that align with client business objectives and industry best practices. This role combines deep technical expertise with strategic thinking to enable Cognizant’s growth in cybersecurity services, with a strong focus on leveraging Artificial Intelligence to solve complex security challenges.
Key Responsibilities
• Solution Design & Architecture
• Develop end-to-end cybersecurity architectures for enterprise, cloud, hybrid, and IoT environments.
• Translate client requirements into robust, compliant, and cost-effective security solutions.
• Lead architecture reviews for Zero Trust, Network Security, IAM, Data Protection, Threat & Vulnerability Management, and Cloud Security.
• Integrate and leverage AI for Cyber Security, utilizing platforms like Gemini, Microsoft Copilot, and Claude to enhance outputs and solution design.
• Work closely with technology vendors for collaboration on services offerings creation and reference architecture.
• Support RFP/RFI responses and create compelling solution narratives.
• Collaborate with sales and delivery teams to shape proposals and transformation roadmaps.
• Conduct workshops and create and deliver compelling presentations for clients on emerging security trends.
• Ensure solutions adhere to regulatory frameworks (NIST, ISO 27001, GDPR, HIPAA).
• Drive security risk assessments and compliance audits for proposed architectures.
• Stay ahead of industry trends such as Post-Quantum Cryptography, AI-driven security, SASE, and IoT Security.
• Evangelize Cognizant’s cybersecurity offerings and contribute to practice growth initiatives.
Required Skills & Expertise
• Technical Skills
• Strong knowledge of cybersecurity principles, Zero Trust, IAM, Data Security, Cloud Security, PKI, and cryptography.
• Expertise in AI for Cyber Security and familiarity with leveraging large language models (e.g., Gemini, Microsoft Copilot) for security use cases.
• Expertise in cloud security (AWS, Azure, GCP) and security architecture frameworks (SABSA, TOGAF).
• Knowledge of emerging areas like Post-Quantum Cryptography and IoT Security.
• Certifications
• Preferred: CISSP, CCSP, CISM, or equivalent.
• Recommended: Cloud security certifications (AWS/Azure/GCP Security Specialty).
• Soft Skills
• Excellent communication and stakeholder management.
• Proven capability to create high-quality presentations and present complex technical solutions effectively to both technical and non-technical client stakeholders.
• Ability to articulate complex technologies and security concepts in a clear, concise, and easy-to-understand manner.
• Ability to lead and co-ordinate with cross-functional teams and drive consensus.
• Analytical thinking and problem-solving under pressure.
Experience
• 12–18 years in cybersecurity with at least 5 years in solution architecture.
• Proven track record in designing enterprise security solutions and leading large-scale transformation programs.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Java Unit Testing Frameworks (Junit| *Unit| *Mock| Cactus| etc)~Digital / Assurance : Mobile Application Testing
Role Descriptions: Test Analyst - Design and execute functional and regression tests for OSSBSS and mobile apps. Document defects and support UAT with business validations. Hands-on experience with Telecom OSSBSS systems is highly desirable.
Essential Skills: Test Analyst - Design and execute functional and regression tests for OSSBSS and mobile apps. Document defects and support UAT with business validations. Hands-on experience with Telecom OSSBSS systems is highly desirable.
Responsibilities
Role Descriptions: Test Analyst - Design and execute functional and regression tests for OSSBSS and mobile apps. Document defects and support UAT with business validations. Hands-on experience with Telecom OSSBSS systems is highly desirable.
Essential Skills: Test Analyst - Design and execute functional and regression tests for OSSBSS and mobile apps. Document defects and support UAT with business validations. Hands-on experience with Telecom OSSBSS systems is highly desirable.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Role Category :Programming & Design
Role : Java Unit Testing Frameworks (Junit| *Unit| *Mock| Cactus| etc)~Digital / Assurance : Mobile Application Testing
