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Director – Solution Architect (Gen AI)

Antal Internationalbangalore, India

1 day ago

Job description

About the Role

We are seeking a seasoned Director-level Solution Architect with deep expertise in Data Science, Classical Machine Learning, and Generative AI to lead strategic client engagements and solutioning for high-impact AI-driven transformation programs. You will work closely with business stakeholders, data engineering teams, and delivery leads to design scalable, value-driven AI / ML / GenAI solutions across industries.

Key Responsibilities

Client Engagement & Pre-Sales

Act as a trusted advisor to CxOs and business leaders during solutioning and proposal stages

Translate business problems into AI / ML / GenAI solution architectures

Drive technical discussions, effort estimations, and proposal development

Solution Design & Architecture

Architect enterprise-scale data science and AI solutions including GenAI, NLP, computer vision, and ML models

Build solution frameworks combining classical ML models , deep learning , LLMs , multi-modal models , and prompt engineering

Ensure performance, scalability, and responsible AI principles are embedded into architecture

Thought Leadership & Strategy

Drive innovation initiatives around GenAI use cases and accelerators

Stay up to date with the latest in LLMs (e.g., GPT, Claude, LLaMA), open-source tooling, and AI safety

Represent the organization in conferences, webinars, and thought leadership publications

Team Leadership

Lead cross-functional solutioning teams including data scientists, ML engineers, cloud architects, and analysts

Mentor senior architects and technologists to grow internal capability

Required Skills and Experience

16–20 years of experience in data science, AI / ML solutioning, and architecture

Strong foundation in classical ML algorithms , statistical modeling, supervised & unsupervised learning

Proven track record in delivering production-grade AI / ML models and pipelines

3+ years hands-on or strategic experience with GenAI / LLMs , including use case design, model selection, fine-tuning, and deployment

Deep understanding of cloud platforms (AWS, Azure, GCP) and MLOps frameworks

Exposure to tools like LangChain, Hugging Face, OpenAI APIs, vector DBs (FAISS, Pinecone, etc.)

Strong knowledge of Python , data science libraries (pandas, scikit-learn, transformers), and orchestration tools (Airflow, MLflow)

Experience working across BFSI, Retail, Healthcare, or Manufacturing preferred

Excellent stakeholder management, storytelling, and communication skills

Preferred Qualifications

Certifications in cloud (AWS / Azure / GCP), data science, or GenAI tools

Experience with RAG pipelines, fine-tuning open-source LLMs, or building GenAI copilots

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