Experience: 10+ years in data science / ML engineering, with 3+ years in a lead or architect role
Education: Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree preferred.
Location: Bangalore
About the Role :
We are looking for an AI Architect to lead our AI & Data Science function and drive the AI strategy for our Customer Data Platform (CDP). You will own the vision, architecture, and delivery of AI/ML capabilities that transform how enterprise clients understand and engage with their customers.
Build and lead a small high impact team and be accountable for shipping production AI features that directly impact client outcomes. If you enjoy working at the intersection of AI, large-scale data systems, and real business impact, this role is for you.
What You Will Do
Define the AI/ML strategy and roadmap for the CDP, aligned with product and business goals
Build and lead the Data Science team — hire, mentor, and grow AI/ML talent
Design and build AI-powered automation for client data onboarding and schema mapping — reducing manual effort and accelerating time-to-value
Develop customer segmentation, clustering, and look-alike modeling capabilities
Build predictive models for customer behaviour — churn prediction, conversion propensity, next-best-action recommendations
Design NLP-powered capabilities for natural language querying and automated insight generation
Develop identity resolution and entity matching algorithms to unify customer profiles across data sources
Own the full model lifecycle — training, evaluation, deployment, monitoring, and retraining in production
Integrate AI/ML models into the core platform and client-facing applications
Collaborate with engineering teams to ensure clean, structured data pipelines for model training and feature engineering
Work with client-facing engineers to understand real-world use cases and translate them into AI solutions
Partner with Product Management to identify high-impact AI opportunities and prioritize the roadmap
What You Bring (Must-Have)
10+ years in data science / ML engineering, with 3+ years in a lead or architect role
Deep expertise in building and deploying production ML systems — not just research or notebooks
Strong experience with LLMs and AI agents — RAG, prompt engineering, agentic frameworks
Proficiency in Python, with hands-on experience in ML frameworks (PyTorch, TensorFlow, scikit-learn)
Experience building NLP systems — text classification, entity extraction, semantic search, embeddings
Strong understanding of data engineering fundamentals — feature stores, data pipelines, data quality
Experience with model deployment and serving in production environments
Experience with vector databases and retrieval-augmented generation (RAG) patterns
Proven ability to build and lead a small, high-impact team
Strong communication skills — ability to translate AI capabilities into business outcomes for non-technical stakeholders
Nice to Have
Experience in CDP, MarTech, AdTech, or customer analytics platforms
Knowledge of customer identity resolution — probabilistic and deterministic matching techniques
Experience with customer segmentation, attribution modeling, or recommendation systems at scale
Background in working with enterprise clients in regulated industries
Experience with cloud-based ML platforms (SageMaker, Vertex AI, or similar)
Familiarity with data warehouses (Snowflake, BigQuery) and streaming systems (Kafka)
