Experience: 17 25 Years
Location: Bangalore & Chennai
Job Type: FullTime
Position Overview:
We are seeking an experienced and highly skilled Generative AI Expert to join our team. The ideal candidate
will have extensive experience in AI/ML engineering data engineering and platform development across
multicloud hybrid environments. You will be responsible for the architecture design and implementation of
Generative AI solutions aimed at improving customer experience personalization and revenue growth.
Qualifications:
17 years of experience in Software Engineering 7 Years into AI/ML 4 Years into data engineering
and platform development.
Masters or equivalent degree in Computer Science Engineering or related fields (preferred).
Certifications in Generative AI Cloud Computing and Data Engineering are highly preferred.
Proven track record of successfully delivering AI/ML industrialization projects with a focus on realtime
and edge AI solutions.
Key Responsibilities:
Lead Generative AI Initiatives: Lead the development of Generative AI strategies from ideation to
deployment leveraging advanced AI/ML technologies.
AI/ML Engineering: Design and implement realtime AI and ML pipelines for feature engineering
model training and model inferencing.
GenAI Centre of Excellence (CoE): Spearhead the establishment and development of GenAI CoE
developing industryspecific archetypes patterns and best practices for AI industrialization.
Platform & Cloud Architecture: Architect and design cloudnative platforms that enable data
integration batch processing realtime streaming and model inferencing.
Model and Data Observability: Champion model performance tracking model explainability and
selfhealing AI systems.
Data Engineering: Lead efforts to architect and develop complex data pipelines using cuttingedge
technologies like inmemory data grids and knowledge graph pipelines.
Realtime ML & Edge AI: Develop realtime eventdriven AI models including clustering similarity
search and embedding models for personalized recommendations and customer insights.
AI/ML Platform Enablement: Drive the deployment of AI/ML platformsasaservice integrating
advanced ML tools and frameworks such as TensorFlow PyTorch Scikitlearn and Seldon Core.
Collaborative Innovation: Collaborate with crossfunctional teams and external partners to define and
implement cuttingedge AI/ML strategies that drive innovation.
AI Product Innovation: Lead AI product asset cohorts including patent filing disclosures and actively
contribute to hackathons innovation cohorts and building accelerators for improved business
outcomes.
Cloud Data Engineering & Platform Strategy: Enable cloud and onprem hybrid solutions for AI model
integration and data transformation working with tools like AWS Azure GCP and Snowflake.
Required Technical Skills:
Generative AI Expertise:
Deep understanding of Generative AI concepts including transformers GANs (Generative
Adversarial Networks) and autoregressive models.
Experience in deploying realtime and batch ML models for productionscale applications
leveraging modern ML/DL frameworks.
Experience in advanced deep learning techniques including Clustering Similarity Search
Embeddings and RNN (LSTM).
AI/ML Frameworks and Tools:
Proficiency in TensorFlow PyTorch Scikitlearn Keras and Hugging Face for building and
deploying models.
Expertise in AI/ML platforms like Domino Weights & Biases DataRobot Comet ML and
Seldon Core for continuous monitoring evaluation and deployment of models.
Knowledge of model interpretability and explainability techniques such as SHAP and LIME.
Cloud and Data Platform Expertise:
Advanced experience in multicloud platforms including AWS Azure and GCP.
Experience with Data Lakes Data Warehouses Feature Stores and Data Integration
platforms like Talend Cloud Apache Kafka and Apache Ignite.
Expertise in cloudnative architectures containerization (Kubernetes Docker) and CI/CD
pipelines for AI/ML workflows.
Data Engineering & Architecture:
Proficiency in Big Data technologies such as Hadoop Spark and NoSQL databases
(MongoDB Cassandra Redis Teradata).
Experience with streaming data solutions like Apache Kafka Google Pub/Sub and realtime
data processing tools.
Knowledge of data modeling ETL and data transformation across complex enterprise
systems including legacy systems modernization.
Advanced Programming Skills:
Strong proficiency in Python Java Scala and experience with Airflow for orchestrating AI/ML
pipelines.
Familiarity with Flask or FastAPI for model inference and API deployment.
AI Democratization & Selfservice Enablement:
Experience in creating selfservice platforms for data scientists and business teams to train
deploy and monitor models using tools like Domino Comet or DataRobot.
Experience in automating and scaling model deployment pipelines using tools like Docker
Kubernetes CI/CD systems and MLflow.
Soft Skills:
Strong leadership abilities with experience driving AI/ML innovation in large organizations.
Excellent communication skills for interacting with stakeholders customers and internal teams.
Experience in fostering a culture of innovation team collaboration and continuous learning.
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Director - Generative AI
