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About the Role
We are seeking a Lead Data Scientist – Agentic AI to spearhead the design, development, and productization of advanced Agentic AI, Generative AI, Machine Learning, and Advanced Analytics solutions. This hands-on technical leadership role requires end-to-end ownership of complex problems, from business understanding to solution deployment and team mentoring.
Responsibilities
- Lead the design and development of production-grade AI agents and agentic workflows.
- Design agent architectures involving LLMs, tools, APIs, databases, business systems, and external services.
- Build and orchestrate multi-agent systems for complex analytical and business workflows.
- Design agent capabilities including tool calling, memory, state management, planning, reasoning and workflow execution.
- Build enterprise-grade RAG solutions and retrieval architectures.
- Develop frameworks to evaluate AI systems for accuracy, groundedness, reliability, consistency and business relevance.
- Identify and address hallucinations, failure modes and reliability issues in agentic applications.
- Evaluate emerging Agentic AI technologies and determine their practical application to business problems.
- Lead the application of Statistics, Machine Learning, predictive modelling and optimization to complex business problems.
- Design analytical approaches for large and complex datasets.
- Develop, validate and optimize ML models.
- Establish robust model validation and performance measurement frameworks.
- Translate analytical outputs into actionable business recommendations.
- Guide Data Scientists in selecting appropriate modelling approaches based on business objectives and data characteristics.
- Apply forecasting and predictive analytics techniques to business problems involving demand forecasting, supply chain & inventory, pricing & promotions, category management, and shopper/customer analytics.
- Guide the team in developing scalable forecasting and predictive solutions.
- Design end-to-end AI architectures covering Data Science, LLMs, agents, APIs, databases and deployment infrastructure.
- Develop backend services using Python, Fast API or equivalent frameworks.
- Integrate ML models, LLMs, databases, APIs and external tools.
- Review technical implementations for scalability, maintainability and performance.
- Establish reusable engineering patterns and best practices for AI applications.
- Take AI/ML solutions from prototype to production.
- Containerize applications using Docker.
- Deploy AI solutions on AWS, Azure or GCP.
- Work with Platform/DevOps teams on scalable AI architecture.
- Contribute to CI/CD, monitoring, logging and production reliability.
- Diagnose production issues and drive improvements in system performance and reliability.
- Own complex AI problems from problem definition through production.
- Break ambiguous business problems into executable technical components.
- Mentor and guide Data Scientists and AI Engineers.
- Review modelling approaches, AI architectures and technical implementations.
- Establish technical standards and reusable components.
- Collaborate with Data Engineering, Software Engineering and DevOps teams.
- Work directly with business stakeholders and clients when required.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related discipline.
- 8+ years of experience in Data Science, Machine Learning, AI, GenAI or related areas.
- Strong foundation in Statistics, Machine Learning and Data Science.
- Strong hands-on experience with Python and SQL.
- Significant experience with Generative AI / LLM applications.
- Strong understanding and practical experience with RAG, Embeddings, Tool calling, Agent orchestration, Agent memory/state, LLM evaluation, AI agents / agentic workflows.
- Experience designing and building production-grade AI systems.
- Experience developing APIs/backend services using FastAPI or similar frameworks.
- Experience with relational databases such as PostgreSQL.
- Hands-on experience with Docker and at least one cloud platform – AWS, Azure or GCP.
- Strong problem-solving and analytical ability.
- Ability to independently own complex technical problems and drive them to completion.
- Demonstrated ability to mentor and technically guide other Data Scientists.
- Client exposure: Regular client visits; leads discovery and proposal sessions.
- Leadership & management: Allocates DS/JDS/SDS across engagements; owns admin and utilisation.
Skills
- Python
- SQL
- Generative AI
- LLM
- RAG
- Embeddings
- Tool calling
- Agent orchestration
- Agent memory/state
- LLM evaluation
- AI agents
- Agentic workflows
- FastAPI
- PostgreSQL
- Docker
- AWS
- Azure
- GCP
- Forecasting
- Time-Series Modelling
- Demand forecasting
- Demand planning
- CPG
- Retail
- Supply Chain
- LangGraph
- LangChain
- Vector databases
- Multi-agent systems
- Guardrails
- AI reliability
- LLMOps
- MLOps
- GenAIOps
- Kubernetes
- ECS
- EKS
- Redis
- Kafka
- RabbitMQ
- Celery
- Terraform
Work Type
- Full-Time
- Permanent
Experience Level
- 8+ Years
Education Level
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related discipline
Benefits
- Comprehensive private medical coverage with Vitality healthcare (includes optical, dental cover, and extended to family members at no extra cost).
- Active Rewards: Earn points with Vitality for benefits like cinema tickets, free coffees, gym discounts.
- 25 days annual leave plus additional loyalty days earned over time.
- Personal charity day: An extra paid day off each year to support a cause, with donation matching.
- Unlimited access to the Champion Health app for physical and mental wellbeing.
- Professional and wellness seminars for development.
- Paid Wellbeing Days for resetting and recharging.
About the Company
- At Aria, we’re not just building a team but fostering a community that values health, purpose, and balance. Join us and experience the difference.