Lead II - Software Engineering - Gen AI Lead

Key Responsibilities GenAI Strategy & Solutioning Define and drive GenAI architecture and roadmap aligned with Customer business priorities Identify high-impact use cases across: Energy & Sustainability (ESG / EST) Real estate operations Data platforms & analytics SDLC automation Workflow automation (e.g., Origami, maintenance workflows) Design end-to-end AI/ML/GenAI solutions using enterprise-grade architecture Architecture & Design Build scalable solutions using: OpenAI stack (Responses API, Agents SDK, function calling, RAG) Dataiku (ML pipelines, GenAI apps, automation) Cloud platforms (Azure/AWS/GCP) Data platforms (Snowflake, Databricks, etc.) Design: Agentic AI systems RAG-based enterprise knowledge solutions AI-driven automation platforms Define integration patterns with: APIs Enterprise systems (ServiceNow, Jira, Origami, Sigma, Tableau, etc.) Stakeholder Engagement Collaborate with: Business teams Customer stakeholders Engineering & data teams Translate business problems into technical AI solutions Present solution proposals, architecture, and PoCs to leadership and clients Delivery & Execution Drive solutions from: Idea PoC MVP Production Lead technical design reviews and governance Ensure scalability, security, and compliance Mentor teams on GenAI best practices Innovation & Proactive Solutioning Continuously identify opportunities for: Cost optimization (e.g., license reduction use cases, operations effort) Process automation AI-driven insights Build reusable frameworks: AI agents Automation accelerators Migration tools (e.g., Tableau Sigma, Tosca AI testing) Required Skills & Experience Core Technical Skills Strong experience in: Solution Architecture / Technical Architecture AI/ML and GenAI systems Hands-on with: OpenAI / LLM ecosystems (RAG, agents, prompt engineering) Python / APIs / microservices Cloud (AWS preferred) GenAI & Data Stack Experience with: OpenAI APIs (Agents, function calling, embeddings) Dataiku or similar ML platforms Vector databases / embeddings Data platforms (Snowflake, Databricks) Integration & Enterprise Systems Experience integrating with: REST APIs Enterprise tools (Jira, ServiceNow, BI tools, etc.) Understanding of: Data pipelines ETL/ELT workflows Domain (Preferred) Experience in: Real estate / logistics / infrastructure Energy & sustainability (ESG, GRESB, CDP, BRSR) Portfolio-level analytics Soft Skills Strong communication & storytelling skills Ability to present to senior stakeholders Proactive mindset with strong problem-solving ability Experience working with cross-functional global teams Good to Have Experience with: Agentic AI frameworks Automation platforms (RPA, workflow tools) BI migrations (Tableau Sigma, etc.) Test automation (Tosca, Playwright, etc.) Knowledge of: ESG reporting frameworks (GRESB, CDP, BRSR) Key Success Metrics Number of GenAI use cases converted to production Business impact (cost savings, efficiency gains) Adoption of AI solutions across portfolio Stakeholder satisfaction and engagement Reusability of frameworks and accelerators Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.