Noida, Up Engineer java architecture Jobs – 142 Open Jobs Today

Campus-Beginner
HCLTech —Gautam Budh Nagar, Uttar Pradesh
- DevOps
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13h
Campus-Competent
HCLTech —Gautam Budh Nagar, Uttar Pradesh
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Techneplus —Noida, Uttar Pradesh
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HCLTech —Gautam Budh Nagar, Uttar Pradesh
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Campus-Beginner

HCLTech -
Gautam Budh Nagar, Uttar Pradesh

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Job details

13 hours ago

Qualifications

DevOps
English
Java
AWS
Project management
Bachelor's degree
Machine learning
Natural language processing
Scrum
Software development
APIs
Agile
VMWare
Linux
AI
Communication skills
Python

Full job description

Gautam Buddha Nagar, Uttar Pradesh
Job Summary

The graduate AI Engineer is responsible for developing innovative technical solutions, integrating generative AI technologies. This graduate role requires a basic understanding of modern technical and cloud-native practices, AI, and DevOps. You will support a wide range of customers through the “Ideation to MVP” journey, demonstrating eagerness to learn and contribute to a dynamic and innovative team.

Key Responsibilities

Key Responsibilities Technical & Engineering Leadership • Develop solutions leveraging GenAI technologies, integrating AI capabilities into cloud-native architectures. • Assist in the design and implementation of GenAI-driven applications, ensuring integration with microservices and container-based environments. • Create solutions that leverage the capabilities of modern microservice and container-based environments running in public, private, and hybrid clouds. • Collaborate on technical projects with partners, including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware. Service Delivery • Support the engineering of GenAI solutions from ideation to MVP, ensuring performance and reliability within cloud-native frameworks. • Assist in optimizing AI models for deployment in cloud environments, balancing efficiency and effectiveness to meet client requirements and industry standards. • Contribute to the assessment of existing solutions and recommend technical treatments to transform applications with cloud-native/12-factor characteristics. 1 Innovation & Initiative • Support the adoption of GenAI technologies within cloud-native projects, enhancing AI integration in cloud services. • Engage in technical innovation and support HCL’s position as an industry leader. • Contribute to authoring whitepapers, blogs, and speaking at industry events. • Maintain hands-on technical credibility, stay ahead of industry trends, and contribute to team learning. Client Relationships • Assist in providing guidance to clients on incorporating GenAI and machine learning into their cloud native systems, ensuring best practices and strategic alignment with business goals. • Participate in workshops and briefings to educate clients on the benefits and applications of GenAI, establishing strong, trust-based relationships. • Contribute to technical projects (PoCs and MVPs) with a focus on technical excellence and on-time delivery.

Skill Requirements

Mandatory Skills & Experience • A newly graduated developer with experience in Java or Python. • Basic understanding of software development and exposure to AI/ML technologies. • Knowledge of GenAI frameworks: Familiarity with using GenAI frameworks and libraries such as OpenAI API. • Understanding of prompt engineering: Basic experience in designing and optimizing prompts for AI models to achieve desired outputs. • Strong verbal and written communication skills (English). • Positive and solution-oriented mindset. • Willingness to learn and grow within an Agile and Scrum project management environment. Desired Skills & Experience • Basic understanding of NLP techniques and tools, including tokenization, embeddings, transformers, and language models. • Interest in data engineering for AI: Eagerness to learn about data preprocessing, feature engineering, and creating pipelines to feed AI models with high-quality data. • Familiarity with AI ethics and bias mitigation: Knowledgeable about ethical considerations in AI and eager to implement strategies to mitigate bias. • Basic understanding of cloud-native technologies and DevOps practices. Willingness to pursue cloud and technical certifications, ideally including AI/ML specializations from providers like Google, Microsoft, AWS, Linux Foundation, IBM, or Red Hat.

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