Senior Consultant

JOB DESCRIPTION

Location: Pune / Bangalore

Join us as a AI Architect within the AI Engineering Division of DAAS (Data AI & Analytics Services)The role focuses on the design and enablement of AI-powered and agentic systems with a particular emphasis on leading architectural design for managing AI risks and controls in compliance with industry define architecture patterns guide delivery teams and work closely with security engineering product and data colleagues to bring intelligent assistants copilots and workflow-optimising AI systems to life.

Technical Skills:

Expertise is required in the following fields:

• Strong understanding of AI Gov Ops and AI Observability market landscape (such as solutions frameworks and libraries) and architectural approaches to implementation of preventative detective and corrective AI risk controls.
• Working knowledge of AI governance frameworks such as ISO/IEC 42001 NIST AI RMF or EU AI Act and an understanding of responsible AI frameworks and ethical principles for design
• Strong solution architecture experience in enterprise environments ideally spanning cloud data API integration and business applications
• Experience designing and/or integrating AI-powered systems into operational workflows including intelligent assistants generative search intelligent summarisation automation platforms or AI-enabled UIs
• Knowledge of GenAI models and GenAI application patterns including retrieval-augmented generation (RAG) and agent-based architectures and orchestration frameworks
• Experience with messaging technologies event mesh concepts and API-driven integration
• Strong stakeholder engagement skills; ability to work across architecture security business engineering and data teams (data protection data risks AI governance) to shape pragmatic future-facing AI solutions
• Proven experience with Azure-native services such as Azure OpenAI Azure ML Cognitive Search Microsoft 365 extensibility Azure Databricks; or alternatives
• Knowledge of architectural patterns for secure access to both structured and unstructured data including classification masking and policy enforcement
• As a precondition of employment for this role you must be eligible and authorised to work in the United Kingdom.

What You will be Doing

• Defining and evolving the enterprise GenAI and broader AI architecture roadmap aligned with AXAs data and digital strategy.
• Leading the architectural design of an enterprise AI Trust and Controls layer to manage AI Trust risks such as Data risks (e.g. toxicity sensitive data leakage) Prompting risks (e.g. prompt injection jail breaking) Application and Security risks (e.g. insecure output handling poisoned model usage) etc.
• Innovating and reimagining business processes to take competitive advantage via the use of AI.
• Leading the design of enterprise solutions that embed LLMs GenAI and agentic automation into business workflows.
• Ability to liaise with integration teams to support design and delivery end-to-end across structured and unstructured data sources and platforms such as Databricks Microsoft 365 SharePoint Salesforce Guidewire ServiceNow Workday etc.
  
  
• Providing technical leadership and guidance for pilot and solution delivery teams building reference implementations and scaling successful patterns
• Partnering with security platform and engineering teams to enable LLMOps and AgenticOps capabilities prompt lifecycle management model observability caching evaluation and governance.
• Contributing to the growth of an AI-ready architecture practice within AXA including knowledge sharing and reference implementation development
• Collaborating with business teams to identify and shape use cases for AI-powered automation intelligent summarisation triage classification and advisory systems
• Supporting integration with messaging systems event-driven architectures and API ecosystems as part of AI solution delivery

Soft Skills:

• Excellent communication skills to facilitate collaboration between business stakeholders and technical teams.
• Strong analytical and problem-solving skills with a focus on optimizing ML workflows.
• Ability to work effectively in a global multidisciplinary team environment.
• Autonomy and innovation capability to advance MLOps practices within the organization.

Background and Experience:

• 12 years of hands-on experience on AI Engineering projectswith a particular emphasis on leading architectural design for managing AI risks and controls in compliance
• Experience with Cloud preferably Azure tools and services specifically tailored for LLMOps.

Required Experience:

Senior IC