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

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