Senior Manager- GenAI Architect

Location: Bengaluru

About Tredence:
Tredence is a global data science solutions provider founded in 2013 by   Shub Bhowmick, Sumit Mehra, and Shashank Dubey   focused on solving the last-mile problem in AI. Headquartered in San Jose, California, the company embraces a vertical-first approach and an outcome-driven mindset to help clients win and accelerate value realization from their analytics investments. The aim is to bridge the gap between insight delivery and value realization by providing customers with a differentiated approach to data and analytics through tailor-made solutions.

Tredence is 4500-plus employees strong with offices in San Jose, Foster City, Chicago, London, Toronto, and Bangalore, with the largest companies in retail, CPG, hi-tech, telecom, healthcare, travel, and industrials as clients.

About the Role
We are looking for an experienced and visionary   Senior      Generative AI Architect   with 12+ years of experience in AI/ML, including hands-on work with   LLMs (Large Language Models)  and   Generative AI solutions   . In this strategic technical leadership role, you will be responsible for designing and overseeing the development of advanced GenAI platforms and solutions that transform business operations and customer experiences.
As the GenAI Architect, you will work closely with data scientists, ML engineers, product teams, and stakeholders to conceptualize, prototype, and scale generative AI use cases across the organization or client engagements.

Key Responsibilities
GenAI Solution Architecture & Design

· Lead the design and development of scalable   GenAI solutions   leveraging   LLMs   ,   diffusion models   , and   multimodal architectures   .

· Architect end-to-end pipelines involving   prompt engineering   ,   vector databases   ,   retrieval-augmented generation (RAG)  , and   LLM fine-tuning   .

· Select and integrate foundational models (e.g.,   GPT, Claude, LLaMA, Mistral  ) based on business needs and technical constraints.
Technical Strategy & Leadership

· Define   GenAI architecture blueprints, best practices, and reusable components   for rapid development and experimentation.

· Guide teams on   model evaluation, inference optimization   , and   cost-effective scaling strategies   .

· Stay current on the rapidly evolving GenAI landscape and assess emerging tools, APIs, and frameworks.

Collaboration & Delivery

· Work with product owners, business leaders, and data teams to identify   high-impact GenAI use cases   across domains like customer support, content generation, document understanding, and code generation.

· Support   PoCs, pilots, and production deployments   of GenAI models in secure, compliant environments.

· Collaborate with MLOps and cloud teams to enable   continuous delivery, monitoring, and governance   of GenAI systems.

Required Qualifications & Experience

·

Education:

Bachelor’s or master’s degree in computer science   , Artificial Intelligence, Data Science, or related technical field   . PhD is a plus.

·

Experience:

12–15 years in AI/ML and software engineering, with  3+ years focused on Generative AI and LLM-based architectures   .

Core Skills

· Deep expertise in   machine learning   ,   natural language processing (NLP)  , and   deep learning architecture   .

· Hands-on experience with   LLMs, transformers, fine-tuning techniques (LoRA, PEFT)  , and   prompt engineering   .

· Proficient in   Python   , with libraries/frameworks such as   Hugging Face Transformers, Lang Chain, OpenAI API, PyTorch, Tensor Flow   .

· Experience with   vector databases   (e.g., Pinecone, FAISS, Weaviate) and   RAG pipelines   .

· Strong understanding of   cloud-native AI architectures   (AWS/GCP/Azure), containerization (Docker/Kubernetes), and API integration.

Architectural & Leadership Skills

· Proven ability to design and deliver   scalable, secure, and efficient GenAI systems   .

· Strong communication skills for cross-functional collaboration and stakeholder engagement.a

· Ability to mentor engineering teams and drive innovation across the AI/ML ecosystem.
Nice-to-Have

· Experience with   multimodal models   (text + image/audio/video).

· Knowledge of   AI governance, ethical AI, and compliance frameworks   .

· Familiarity with   MLOps practices for GenAI   , including model versioning, drift detection, and performance monitoring.

Skills

Python, GenAI, System Design and Architecture, RAG, LLM, Agentic