Senior Staff Engineer - AI

Overview

Senior AI Engineer role combining classical analytics, data engineering and AI-native ways of working to design and deliver enterprise-scalable AI frameworks, agents and RAG solutions that drive measurable business KPIs, while acting as an emerging AI Coach for the analytics community.

What you'll do

• Find, interpret and merge data sources, ensure dataset consistency, create visualisations and communicate insights simply, using AI-augmented tooling (Claude Code, GitHub Copilot, LLM analytics assistants).
• Prioritise, prototype, design, build, test and deploy analytics models and AI agents in an agile methodology, including RAG on enterprise data, natural-language querying, and LLM-driven data quality and anomaly detection.
• Develop analytic/AI solutions from various source systems, augmented with AI-assisted profiling, entity resolution and quality-check pipelines.
• Develop technical expertise in AI development for engineering applications, including next-generation 'ask-the-data' experiences powered by LLMs on the enterprise Data Fabric.
• Present project plans, technical roadmaps, risks and recommendations to senior leaders, including AI/analytics adoption roadmaps tied to measurable business KPIs.
• Work closely with Engineering teams and AI leadership to identify AI-enabled analytics use-cases (agents, copilots, conversational dashboards) and translate AI-driven insights into business language for non-technical stakeholders.
• Serve as a technical specialist with deep expertise in classical analytics and applied AI/ML for enterprise data.
• Partner closely with FLIGHT DECK and business-defined priorities to build, scale and industrialise AI-powered analytics workflows, agents and connectors end-to-end to production adoption.
• Define and enforce enterprise-grade AI standards, guardrails and best practices (responsible AI, evaluation, security, observability).
• Coach and enable AI Builders across the analytics community: teach AI Foundations, review agents and workflows, unblock architectural barriers, and align team practices with Data Fabric standards.
• Develop communication, training and change-management deliverables to increase adoption of analytics and AI capabilities; establish a community of practice around AI-augmented analytics.

What you'll need

• Bachelor's in Engineering/Technology/Aerospace or STEM majors, with a minimum of 8 years of experience.
• Strong oral and written communication skills; strong interpersonal and leadership skills.
• Demonstrated ability to lead programs and projects: document, plan, market and execute end-to-end; established project-management skills.
• Demonstrated ability to analyse and resolve problems, including framing ambiguous business questions as AI/analytics problems and back.
• Strong SQL/Python fundamentals plus fluency in AI-augmented development, using AI as a productivity multiplier without compromising data correctness, lineage or governance.
• Hands-on with modern AI development tooling: GitHub Copilot, Claude Code, LLM orchestration frameworks, agent frameworks, vector databases and RAG patterns applied to enterprise data.
• Deep experience building secure and scalable enterprise AI-analytics solutions, deploying connectors, agents and artifacts that enable others to scale AI adoption.
• Cloud proficiency (AWS, GCP, Azure) with data-engineering fundamentals and cybersecurity awareness.
• Coaching mindset: comfortable teaching AI Foundations and lifting the AI capability of analysts and engineers; can support ~6–8 AI Builders.
• Continuous learner who keeps pace with external AI/analytics capabilities and brings insights back to shape enterprise standards and Data Fabric alignment.

Nice to have

• Formal AI/ML certifications: AWS Certified ML, GCP Professional ML Engineer, Azure AI Engineer, Databricks ML.

Details

• Location: Bengaluru (John F. Welch Technology Center).
• Relocation assistance provided.