Technical Lead – Data & AI

Key Responsibilities

Data & AI Expertise

• Architect modern data architectures including data lakes, data warehouses, lakehouses, and real-time streaming platforms
• Design and implement ML/AI systems including model training pipelines, feature stores, model serving infrastructure, and MLOps practices
• Lead the development of advanced analytics solutions leveraging machine learning, deep learning, NLP, computer vision, and generative AI
• Establish data governance frameworks, ensuring data quality, security, privacy, and compliance standards
• Optimize data pipelines and AI models for cost efficiency, performance, and scalability
  

Cloud & Infrastructure

• Architect cloud-native solutions on Azure, AWS, or GCP (multi-cloud experience is a strong plus)
• Lead cloud migration strategies and optimize infrastructure costs while maintaining performance
• Implement security, compliance, and disaster recovery protocols for data platforms
• Design scalable microservices architectures for AI/ML model deployment
  

Artificial Intelligence

• Lead deep learning initiatives for complex problem-solving including computer vision, NLP, and predictive modeling Architect Large Language Model (LLM) solutions and RAG (Retrieval-Augmented Generation) systems
• Develop and fine-tune small language models when appropriate for specialized use cases or cost optimization
• Pioneer Agentic AI systems that can autonomously perform complex tasks and decision-making
• Establish MLOps practices including model versioning, monitoring, and continuous improvement
  

Technical Leadership

• Provide hands-on technical guidance and mentorship to data engineers, data scientists, and ML engineers
• Conduct architecture reviews and ensure adherence to best practices and coding standards
• Stay ahead of emerging technologies and evaluate their applicability to business challenges
• Lead proof-of-concepts and pilot projects for innovative data and AI solutions
• Make critical technical decisions with long-term scalability and maintainability in mind Collaboration
• Translate complex technical architectures into clear, compelling narratives for executive leadership
• Present technical roadmaps, project updates, and ROI analyses to C-level stakeholders
• Collaborate with product managers, business analysts, and domain experts to understand requirements
• Document architectural decisions, technical specifications, and design patterns comprehensively
• Facilitate cross-functional workshops and design thinking sessions
• Represent the organization at industry conferences, meetups, and technical forums
  

Required Technical Skills

Data Engineering & Platforms

• Expert-level proficiency in modern data stack technologies (Snowflake, Databricks, BigQuery, Redshift)
• Deep experience with distributed computing frameworks (Apache Spark, Flink, Kafka)
• Strong knowledge of ETL/ELT tools, data integration patterns, and data modeling techniques
• Expertise in both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, Redis)
  

AI & Machine Learning

• Proven track record of deploying production ML systems at scale
• Strong foundation in machine learning algorithms, deep learning architectures, and statistical modeling
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face)
• Hands-on experience with LLMs, generative AI, and prompt engineering
• Knowledge of MLOps tools and practices (MLflow, Kubeflow, SageMaker, Vertex AI)
• Experience with computer vision, NLP, recommendation systems, or forecasting models
• Knowledge of Agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI)
  

Cloud & Infrastructure

• Extensive experience with cloud platforms (AWS, Azure, or GCP) with deep understanding of data and AI services
• Proficiency in infrastructure as code (Terraform, CloudFormation)
• Experience with containerization and orchestration (Docker, Kubernetes)
• Knowledge of CI/CD pipelines and DevOps practices for data and ML workloads Programming & Development
• Expert-level programming skills in Python and SQL
• Proficiency in at least one additional language (Java, Scala, or Go)
• Strong understanding of software engineering principles, design patterns, and clean code practices
• Experience with version control systems (Git) and collaborative development workflows
  

Required Soft Skills

• Exceptional verbal communication skills with the ability to articulate complex technical concepts to both technical and non-technical audiences
• Outstanding written communication for documentation, technical proposals, and stakeholder reports
• Immediate joiner or maximum 20 days of notice period
  

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