Job Title: Senior Consultant | GEN AI | Bengaluru | SAP
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Your work profile
As a Analyst/Consultant/Sr. Con/Manager in our <SAP TEAM > Team you’ll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations: -
The primary role is to make immediate, direct contributions to enhancing our clients’ competitive position and performance in ways that are distinctive, innovative, and sustainable.
To do this, one must perform the following activities within the firm:
We are seeking a skilled and passionate AI/ML Engineer with expertise in Generative AI (Gen AI) to join our dynamic team. The ideal candidate will have hands-on experience working with large language models (LLMs), frameworks like LangChain and LangGraph, and advanced knowledge of RAG (Retrieval-Augmented Generation) and AI agents. The role demands strong programming skills, problem-solving abilities, and the ability to contribute to cutting-edge AI projects.
Education:
BE/Btech/Bachelor of Engineering/Graduate
Job Title: Senior Consultant – Generative AI
Location: [Location]
Job Type: Full-Time
Key Responsibilities:
AI Solution Design & Implementation:
Lead the development and deployment of generative AI models (e.g., GPT, GANs, VQ-VAE, etc.) for various business applications, including content generation, language processing, automation, and creative tools.
Work with clients to understand their business needs, analyze data, and create tailored AI solutions.
Develop end-to-end AI systems, from data preprocessing to model training and deployment.
Coding & Model Development:
Write efficient, reusable, and scalable code to implement AI models using languages like Python, TensorFlow, PyTorch, etc.
Optimize machine learning algorithms and models for performance, accuracy, and scalability.
Apply best practices for coding, version control, and debugging in AI model development.
Consulting & Client Engagement:
Serve as a subject matter expert in Generative AI, providing guidance and technical expertise to clients.
Assist clients with evaluating their AI maturity and develop roadmaps for AI adoption and implementation.
Conduct workshops and training sessions to help clients understand the potential and practical use of generative AI.
Collaboration & Innovation:
Work collaboratively with Data Scientists, Engineers, and Product Teams to integrate AI solutions into clients’ existing systems.
Continuously research the latest trends in AI and generative models, bringing new insights and innovative solutions to clients.
Contribute to thought leadership by publishing articles, papers, or blogs on generative AI technologies.
Project Management:
Manage project timelines, deliverables, and resources to ensure timely completion of client engagements.
Prepare and present technical reports, documentation, and presentations to stakeholders.
Assist in scoping and defining project requirements, ensuring solutions meet client expectations.
Qualifications:
Education:
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Experience:
4-6 years of professional experience in AI, with a strong focus on generative models and machine learning.
Hands-on experience with implementing generative AI technologies, such as GPT (Generative Pre-trained Transformers), GANs, or other deep learning architectures.
Proficiency in programming languages such as Python, Java, or C++.
Experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch.
Solid understanding of data science, machine learning algorithms, and neural networks.
Skills:
Strong coding skills and the ability to write clean, efficient code for AI and ML model development.
Proficiency with cloud platforms (AWS, Google Cloud, Azure) and tools for deploying AI models in production.
Excellent problem-solving skills and the ability to tackle complex technical challenges.
Strong analytical, communication, and presentation skills.
Preferred:
Experience with NLP models (e.g., BERT, GPT) and generative creative tools (e.g., DALL·E, Stable Diffusion).
Familiarity with MLOps, DevOps, and model deployment pipelines.
Knowledge of AI ethics and governance frameworks.