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Be a part of our success story. Launch offers talented and motivated people the opportunity to do the best work of their lives in a dynamic and growing company. Through competitive salaries, outstanding benefits, internal advancement opportunities, and recognized community involvement, you will have the chance to create a career you can be proud of. Your new trajectory starts here at Launch!

The Role:

Launch is actively seeking a visionary Solutions Architect / Principal Software Engineering Lead (AI) to design and deliver modern engineering and applied AI solutions across client engagements. This role blends deep hands‑on engineering, architectural leadership, AI system design, and client advisory. You will operate across system design, production‑grade engineering, multi‑agent architectures, cloud platform strategy, and the development of Launch’s AI practice.

Responsibilities Include:

Architecture & Technical Strategy

• Define the technical direction for client engagements end-to-end: discovery, design, build, and production hardening.
• Assess client technology ecosystems and identify high-impact opportunities for AI/ML integration.
• Lead architecture reviews, design sessions, and technology selection across cross-functional stakeholder groups.
• Translate ambiguous business problems into concrete engineering plans with clear scope, milestones, and risk callouts.

AI Engineering & Delivery

• Architect production agentic systems including multi-agent orchestration, agent harnesses, skill/tool composition, human-in-the-loop checkpoints, and inter-agent communication protocols (e.g., A2A, MCP).
• Build and govern MCP server ecosystems: design, deploy, and secure Model Context Protocol integrations connecting AI agents to enterprise data sources, internal APIs, and third-party platforms.
• Define agent skill and capability frameworks including reusable skill libraries, prompt engineering standards, and evaluation harnesses for consistent agent behavior across engagements.
• Architect RAG pipelines, fine-tuning workflows, and model lifecycle infrastructure (training, serving, experiment tracking) as foundational components of agentic systems.
• Integrate AI platforms and APIs (Azure OpenAI, Amazon Bedrock, Anthropic, Vertex AI) into production systems with enterprise-grade reliability, cost governance, and observability.
• Establish AI-native development practices: embed tools such as Claude Code, Cursor, and GitHub Copilot into team workflows with standards for AI-assisted code review, test generation, and documentation.
• Design evaluation and observability infrastructure including LLM eval frameworks, red-teaming, behavioral drift detection, and production monitoring across tool call chains, latency, and failure modes.
• Apply responsible AI governance: define guardrails, access controls, and audit patterns for agentic workflows in enterprise environments including scope containment and escalation paths.

Hands-On Engineering

• Write production code and lead by example — this role requires someone who is still close to the code.
• Design cloud-native architectures across multiple hyperscalers (AWS and Azure primarily) microservices, event-driven systems, serverless, and containerized workloads.
• Define and implement infrastructure-as-code using tools such as Terraform, Pulumi, CloudFormation, or Bicep.
• Design and optimize CI/CD pipelines, GitOps workflows, and container orchestration using Docker and Kubernetes.
• Establish observability and reliability practices using tools such as Datadog, Prometheus, Grafana, CloudWatch, or Azure Monitor.
• Drive security-by-design across the delivery lifecycle including IAM, network architecture, secrets management, and compliance automation.

Leadership & Client Advisory

• Lead engineering teams ranging from small squads to 10+ person delivery teams, scaling leadership approach to the needs of each engagement.
• Mentor and develop engineers at all levels through code reviews, pairing, and design coaching.
• Operate as a trusted advisor to client technical leadership and executive stakeholders. Communicate trade-offs clearly and build confidence.
• Influence without direct authority — driving alignment across cross-functional teams through technical credibility and stakeholder management.
• Lead discovery and requirements elicitation, surfacing the underlying business need beyond the stated request.
• Produce clear written artifacts: technical proposals, architecture decision records, SOWs, and executive-level status communication.
• Grow client relationships and identify follow-on opportunities through proposal contributions and delivery-driven account expansion.
• Contribute to Launch's growth — practice development, thought leadership, and hiring.

Qualifications:

Must-Haves:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• 10+ years in software engineering with demonstrated experience in architecture and technical leadership roles.
• 3+ years hands-on with AI/ML in production. Broad fluency across generative AI (LLMs, RAG, fine-tuning, agents), MLOps (model serving, pipelines, experiment tracking), and AI-integrated product development.
• Consulting or client-facing delivery experience with a proven ability to integrate into client organizations and establish credibility with technical and executive stakeholders.
• Full-stack engineering capability across frontend, backend, infrastructure, and data layers. Proficiency in multiple modern languages (e.g., Python, TypeScript/Node.js, C#/.NET, Java, or Go) with the ability to move between them as engagements require.
• Multi-hyperscaler depth across AWS and Azure, including their respective AI/ML service ecosystems (Bedrock, SageMaker, Azure OpenAI, Azure ML). GCP experience is a plus.
• Strong fundamentals in distributed systems, event-driven architecture, API design, and DevOps/platform engineering.
• Experience leading engineering teams in agile delivery environments.
• Business acumen with the ability to connect architecture decisions to cost, timeline, and organizational impact.
• Executive presence and communication skills effective with both technical and non-technical audiences.
• Proven ability to operate in ambiguous environments and adapt to diverse client cultures.

Strong Differentiators

• Experience contributing to the development of AI engineering practices, reusable frameworks, or internal accelerators within a consulting or enterprise environment.
• Experience advising C-suite or VP-level stakeholders on AI strategy, investment prioritization, and organizational readiness.
• Depth with agentic AI frameworks (LangChain, LangGraph, LangSmith, LlamaIndex, Semantic Kernel, CrewAI) and emerging standards like MCP (Model Context Protocol).
• Experience with enterprise data platforms (Databricks, Snowflake, BigQuery) in the context of AI/ML workloads.
• Cloud architecture certifications across AWS and Azure (AWS SA Professional, Azure Solutions Architect Expert).
• Published writing, open-source contributions, or conference speaking that demonstrates thought leadership in AI or software architecture.
• Domain depth in industries such as healthcare, financial services, retail, or public sector.

Compensation & Benefits:

As an employee at Launch, you will grow your skills and experience through a variety of exciting project work (across industries and technologies) with some of the top companies in the world! Our employees receive full benefits—medical, dental, vision, short-term disability, long-term disability, life insurance, and matched 401k. We also have an uncapped, take-what-you-need PTO policy. The anticipated base wage range for this role is $190,000 to $230,000. Education and experience will be highly considered, and we are happy to discuss your wage expectations in more detail throughout our internal interview process.

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Principal AI Security Engineer is a senior technical leader on the AI Security team, responsible for designing, building, and operating security controls for generative AI and Machine Learning (ML) systems across their full lifecycle: data, training, deployment, and runtime.

This role is deeply hands-on: you will work directly with data science, MLOps, platform, devops and application teams to secure LLMs, RAG systems, AI agents, and AI-enabled products. You will also lead the intake and review process for AI use cases, helping the organization adopt AI safely and at scale in a highly regulated environment.

The ideal candidate combines:

* Strong security engineering and cloud architecture experience

* Deep, current familiarity with modern AI/LLM tooling and practices

* Familiar and can cover basic coding within the AI tooling space (python, others)

* The ability to communicate clearly with senior leadership and influence enterprise-wide strategy

Essential Duties and Responsibilities

Secure AI / ML platforms and workloads

* Lead security architecture and threat modeling for AI/ML systems, including LLMs, RAG pipelines, agents, and AI-powered applications.

* Design and implement security controls as code (services, libraries, infrastructure-as-code, policy-as-code) for AI/ML platforms and workloads.

* Lead and help setup the basic infrastructure needed to safely rollout AI - MCPs, LLMs, pipelines, Test harness for AI (ie: harmbench), intake automation.

* Partner with data science and MLOps teams to harden:

• Data ingestion and labeling
• Training and fine-tuning pipelines
• Model registries and deployment workflows
• Inference APIs, agents, and integrations

* Define and champion secure reference architectures and patterns for common AI use cases and focus on composable architecture.

AI use case intake & governance

* Design, implement, and continuously improve the intake, triage, and review process for AI/ML and generative AI use cases across the organization.

* Build and automate self-service workflows (e.g., request forms, risk questionnaires, routing, approvals) that balance speed of delivery with security, privacy, and compliance with a focus on risk scoring and scorecards.

* Define risk-based criteria for AI use case approval, including data sensitivity, model and vendor selection, integration patterns, and control requirements; this will involve in re-mapping the complete end to end lifecycle.

* Review proposed AI solutions from concept through deployment, providing clear, actionable guidance to product and engineering teams.

* Maintain visibility into the AI use case portfolio and risk posture, and provide regular reporting to leadership and governance bodies.

Monitoring, detection & assurance

* Establish and maintain monitoring and detection for AI-specific threats, such as:

• Prompt injection and jailbreak attempts
• Data exfiltration and sensitive data exposure
• Misuse or abuse of AI tools and agents
• Anomalous model or pipeline behavior

* Integrate AI/ML systems with existing logging, SIEM, and incident response processes.

* Lead or participate in AI-focused security assessments, red-teaming, and adversarial testing; drive remediation and verification.

Strategy, leadership & enablement

* Help define and evolve the organization's AI security strategy, standards, and roadmap in partnership with Security, Engineering, Data, Legal, Privacy, and Risk.

* Translate global privacy, data sovereignty, and regulatory requirements into practical technical controls for AI workloads across multiple cloud environments.

* Prepare and deliver executive-ready briefings and narratives on AI security risks, controls, and progress.

* Mentor other engineers and serve as THE internal subject matter expert on AI/ML security, generative AI, and LLM-based systems.

Qualifications Expected for Position

• 7+ years of experience in information security, security engineering, or related fields, including significant time building and securing production systems.
• 3+ years of hands-on experience with AI/ML technologies (such as LLMs, RAG, model training/fine-tuning, MLOps, or AI-powered products), including implementation of security controls or guardrails for these systems.
• Strong programming skills in one or more relevant languages (e.g., Python, TypeScript/JavaScript, Go, or similar), with a track record of contributing to production-grade tools, services, or libraries.
• Deep understanding of cloud security architecture and controls on at least one major cloud platform (AWS, Azure, or GCP), including identity, networking, secrets management, data protection, logging, and monitoring.
• Experience designing and implementing controls in a highly regulated environment; healthcare or financial services preferred.
• Demonstrated ability to lead complex technical initiatives across multiple teams, from problem definition through design, implementation, and adoption.
• Proven ability to communicate complex technical and risk topics clearly to both engineering teams and senior leadership.

Preferred Qualifications:

* Practical experience securing LLM- and genAI-based systems, such as:

• RAG architectures backed by internal data
• AI assistants, copilots, or agents integrated with enterprise tools
• Fine-tuned models and model hosting platforms

* Experience with AI IDE tools

• cursor, windsurfer, others
• Knows the security problems and has practical solutions that balances innovation with innovation.

* Familiarity with AI/ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, Scikit-learn) and/or modern LLM development stacks and IDEs (e.g., API-based LLMs, self-hosted models, AI-enhanced coding tools).

* Experience with:

• Security for data pipelines, feature stores, and model registries
• Detection engineering or SIEM tuning for AI-related events
• Red-teaming or adversarial testing of AI systems

* Evidence of ongoing engagement with AI and security (such as side projects, open-source contributions, lab environments, publications, or conference talks).

* Familiarity with emerging AI security and safety standards and forward-looking industry guidance and horizon reports.

* Relevant certifications (e.g., cloud security, security engineering, or governance) are a plus.

* Strong analytical and problem-solving skills, with the ability to operate effectively in a fast-evolving technical and regulatory landscape.

* High level of integrity and ethical conduct.

This role is a fit if you:

* Regularly build, break, or secure AI/ML or LLM-based systems in your day-to-day work or personal projects.

* Are comfortable reading and writing code, experimenting with new AI tools, and wiring them into real systems.

* Enjoy turning ambiguous AI ideas and risks into concrete architectures, controls, and automation.

* Can move fluidly between deep technical discussions and concise, executive-level explanations.

This role is not a fit if you:

* Prefer to focus solely on policy, governance, or vendor assessments without hands-on technical work.

* Do not actively engage with current AI/LLM tooling, research, and emerging practices.

* "Describe a specific LLM or AI/ML system you have secured. What were the main risks and what controls did you implement?"

* "What AI tools, libraries, or environments do you actively use or experiment with today (work or personal), and for what?"

* "What do you see as the most important AI security or safety developments on the horizon over the next few years, and why?"

The base salary range for this position is$180,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

• 
  
• A typical day will involve a mix of hands-on coding, architectural design, and research.
  
• The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
  
• This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
  
• They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
  

• 
  
• Python
  
• JavaScript/TypeScript
  
• AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
  
• AI Models (e.g. Claude, OpenAI, etc.)
  
• AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
  
• Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
  
• Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
  
• API Design
  

• 
  
• Deep hands-on experience in Python for AI/ML development.
  

• 
  
• Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
  
• Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
  
• Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
  

• 
  
• Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
  
• Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
  
• Experience developing autonomous agents using cloud-based AI services.
  
• Experience with prompt engineering techniques and model fine-tuning.
  
• Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
  
• Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
  

Role Overview

We are seeking a highly experienced Senior AI Architect to lead the design and implementation of enterprise-scale Agentic AI systems and multi-agent orchestration platforms. This role requires deep expertise in LLM-based architectures, distributed systems, and cloud-native infrastructure.

As a technical authority, you will guide enterprise clients through their Agentic AI transformation, from evaluating AI frameworks and communication protocols to deploying scalable, production-ready AI automation solutions.

You will work at the forefront of GenAI platform engineering, designing architectures that power intelligent automation, enterprise knowledge systems, and AI-driven workflows.

Key Responsibilities

Agentic AI Architecture & Design

• Design and implement end-to-end multi-agent orchestration systems for enterprise automation and decision intelligence.
• Define agent design patterns, including agent roles, delegation frameworks, task decomposition, and orchestration strategies.
• Architect scalable agent ecosystems with lifecycle management, monitoring, fallback mechanisms, and human-in-the-loop capabilities.
• Evaluate and implement inter-agent communication protocols such as MCP, A2A, REST, gRPC, JSON-RPC, and event-driven messaging.

GenAI & Foundation Model Integration

• Select and integrate LLMs and foundation models (OpenAI, Anthropic, Gemini, Mistral, Llama, etc.) based on task requirements.
• Develop advanced prompt engineering and context management strategies, including:
• Few-shot prompting
• Chain-of-thought reasoning
• Retrieval-Augmented Generation (RAG)
• Structured output pipelines
• Implement tool and function calling patterns enabling agents to interact with enterprise APIs, databases, and services.
• Optimize context window management, token budgets, and dynamic context injection for scalable production systems.

State Management & Agent Memory

• Architect stateful AI systems with short-term, long-term, and episodic memory layers.
• Implement persistence strategies using:
• Vector databases
• Key-value stores
• Graph databases
• Relational systems
• Design auditable and idempotent execution patterns suitable for enterprise governance and compliance requirements.

Microservices & Platform Engineering

• Build AI platforms using loosely coupled microservices with scalable APIs and observability built in.
• Deploy AI systems using container orchestration platforms such as Kubernetes (EKS, AKS, or GKE).
• Establish CI/CD pipelines for AI workloads including model versioning, prompt versioning, and deployment strategies.
• Promote Infrastructure-as-Code (IaC) using tools like Terraform and GitOps deployment practices.

Enterprise Client Engagement

• Partner with enterprise stakeholders to assess AI readiness and automation opportunities.
• Translate complex business requirements into scalable AI system architectures.
• Provide guidance on build vs. buy decisions for AI frameworks and vendor tools.
• Produce architecture documentation, reference designs, and implementation playbooks.

Required Qualifications

• 8+ years of experience in software engineering or platform architecture.
• 3+ years of experience designing AI/ML systems or GenAI platforms.
• Hands-on experience building multi-agent or agentic AI orchestration systems in production.
• Strong experience with agent frameworks such as:
• LangChain
• LangGraph
• AutoGen
• CrewAI
• Semantic Kernel
• Expertise integrating LLMs, embeddings, tool/function calling, and RAG pipelines.
• Deep knowledge of microservices architecture, distributed systems, and API design.
• Experience with container orchestration (Kubernetes preferred) and cloud platforms such as GCP, AWS, or Azure.
• Strong programming skills in Python, with additional experience in TypeScript, Go, or Java preferred.

Preferred Qualifications

• Experience working with enterprise clients or consulting environments.
• Knowledge of AI governance, responsible AI, and compliance frameworks.
• Familiarity with model fine-tuning, RLHF, or adapter-based model customization.
• Experience with AI observability tools such as LangSmith, Arize AI, or OpenTelemetry.
• Experience working with vector databases (Pinecone, Weaviate, Qdrant, pgvector).
• Contributions to open-source AI or agentic system projects.

Propy is revolutionizing the real estate industry by building the world's first AI-powered Title and Escrow platform onchain. We have processed over $5B in transactions, and we are on a mission to make closing on a home as easy as buying a stock.

We combine blockchain for security with advanced AI to automate the heavy lifting of closing documents. We aren't just "using" AI; we are building the infrastructure that allows AI agents to securely manage escrow, eliminate fraud, and run 24/7.

We are looking for a pragmatic Applied AI Engineer to join our engineering team.

The role is not about training models and does not involve academic Machine Learning research. It is about building the rails that make AI usable in a high-stakes financial environment. You will bridge the gap between our robust C#/.NET architecture and the probabilistic world of LLMs.

Title and Escrow is a document-heavy industry with zero room for error. Your mission is to use AI to clean up the messiness of real-world real estate data.

You will solve problems like:

• Structured Data Extraction: Converting messy, unstructured data (like emails, PDFs, documents)  from various sources into strictly validated JSON schemas with as close to 100% accuracy as possible.
• Escrow Automation: Designing workflows that reduce human intervention by 50% by intelligently routing tasks based on AI analysis.
• Fraud Detection: Implementing deterministic logic checks on bank and financial documents to detect fraud patterns before they happen.

• Engineer the Integration: Writing production-grade code that interacts with external AI APIs
• "Prompt Engineering" as Code: You won't just write prompts; you will version, test, and optimize them. You will define strict schemas to ensure the AI speaks the language of our internal tools.
• Orchestrate & Validate: Help in building the logic that parses AI responses, validates them against our database (MongoDB), and flags inconsistencies before they reach the user.
• Full-Stack Implementation: Work to visualize AI-aided services and data for user review and approval.
• Collaborate: Work closely with the other senior engineers and product owners to translate complex "Title & Escrow" schemas into technical constraints that an AI can understand.

• Developer DNA: You are a software engineer first. You have strong experience in Python (C# / .NET is an advantage) and understand programming in depth. 
• Applied AI Experience: You have integrated LLMs into applications via API. Have experience with not only models but also AI frameworks. Experience with workflows, AI agent building and orchestration. You understand context windows, token limits, temperature, and guardrails.
• Data Handling: Experience with handling complex data structures.
• The "Glue" Mindset: You enjoy writing the code that connects different services ( like the AWS, AI APIs, and Database) to make a seamless features.
• Collaborative Autonomy: You will own the AI domain, but you won't be on an island. You will be embedded in a senior engineering team that supports you with architecture, code reviews, and best practices.

• Experience with AWS infrastructure.
• Familiarity with the US Real Estate, Title, or Escrow process.

• Working in a transparent environment which focuses on solving problems and getting things done.
• The opportunity to work with very smart and driven people.
• The ability to grow your talents and career in a high-growth sector.
• A remuneration package that is based on the candidate's motivation, skills, and experience.

Please submit your resume to this job ad along with a portfolio of your AI-related experience, GitHub account and anything else you find applicable. 

Generative AI Engineer/Agentic Engineer

You bring AI to life - one agent at a time. At BWE, we rely on you to build smart, adaptive systems that act on behalf of our teams, streamlining workflows and amplifying impact. As an Agentic Engineer, you turn complex business tasks into intelligent, automated solutions that drive efficiency across the enterprise. Your work helps us scale AI with confidence, creativity, and control.

Responsibilities:

• Design, build, and optimize autonomous or semi-autonomous AI workflows (agentic systems) using Microsoft Copilot, Power Automate, Copilot Studio, and third-party AI platforms.
• Translate complex business tasks into orchestrated, multi-step AI workflows that can act with minimal user input while maintaining accuracy and compliance standards.
• Develop and iterate intelligent assistants, copilots, and AI agents to automate business processes across origination, closing, servicing, and corporate functions.
• Collaborate with Business Partners and business units to test, refine, and scale agentic tools that drive measurable efficiency improvements and user adoption.
• Lead implementation of BWE's Scale Agentic AI initiative by identifying high-impact automation opportunities and deploying production-ready AI agents.
• Partner with AIOps Engineer to ensure agentic systems integrate properly with monitoring, governance, and optimization frameworks.
• Stay ahead of emerging agentic design patterns, orchestration technologies, and best practices while bringing forward innovative solutions to business challenges.
• Create reusable agentic templates and workflow patterns that enable citizen developers to build AI-powered automation within governance frameworks.
• Implement security and compliance controls for agentic systems ensuring adherence to financial services regulations and data privacy requirements.
• Research and experiment with innovative agentic AI technologies and platforms to enhance BWE's automation capabilities.
• Provide training and support to business users adopting agentic tools and automation workflows.
• Document agentic system architectures, decision logic, and operational procedures for knowledge transfer and maintenance.

Near-Term Deliverables:

• Build and deploy at least 3-5 production agentic systems that demonstrate significant business impact and operational efficiency gains.
• Establish agentic AI development framework including design patterns, testing methodologies, and deployment standards.
• Create a comprehensive library of reusable agentic components and workflow templates that accelerate automation deployment across business functions.
• Partner with Business Partners to identify and prioritize high-impact opportunities for agentic AI implementation with detailed business case analysis.
• Develop agentic system monitoring and optimization practices ensuring reliable performance, accuracy, and cost efficiency.
• Research and recommend emerging agentic AI platforms and technologies for potential adoption with hands-on evaluation and implementation guidance.
• Create citizen developer enablement materials including agentic workflow templates, training resources, and best practice guidelines.
• Establish agentic AI governance practices including approval workflows, risk assessment, and compliance validation procedures.
• Complete advanced training in agentic AI, workflow orchestration, or emerging automation technologies relevant to enterprise applications.
• Contribute to BWE's competitive advantage by pioneering innovative agentic use cases and automation strategies.

Minimum Qualifications:

• 5+ years of experience building AI-driven workflows, intelligent automation, or low-code/no-code solutions in enterprise environments.
• Hands-on experience with Microsoft Power Platform (Power Automate, Power Apps), Microsoft Copilot Studio, and Large Language Model (LLM) integration.
• Strong grasp of prompt engineering, conversation design, logic flows, and business process optimization techniques.
• Experience with API integration, data transformation, and system connectivity for workflow automation.
• Knowledge of agentic AI concepts including multi-step reasoning, tool usage, and autonomous decision-making systems.
• Understanding of business process design, user experience principles, and change management for automation adoption.
• Bachelor's degree in Computer Science, Engineering, Business Technology, or related field, or equivalent work experience.
• Creative, fast-moving builder with prototyping mindset and deep understanding of user needs and business workflows.

Preferred Qualifications:

• Experience with advanced agentic AI platforms and orchestration tools beyond Microsoft ecosystem.
• Knowledge of machine learning, natural language processing, and conversational AI development.
• Familiarity with enterprise integration patterns, API management, and cloud-native application development.
• Experience in CRE, financial services, or regulated industries with complex compliance and audit requirements.
• Understanding of AI governance, responsible AI deployment, and risk management for autonomous systems.
• Previous experience leading automation initiatives or digital transformation projects.
• Knowledge of emerging technologies including multi-modal AI, autonomous agents, and AI orchestration platforms.

AI & Business Systems Manager

Christopher Homes, a nationally acclaimed luxury residential developer and home builder, has been creating Nevada’s finest neighborhoods since 1981. Within four decades, we have developed over 2,000 homes with a total value of over $1 Billion.

Our experience and reputation for developing luxury residential neighborhoods is unmatched. Of note, Christopher Homes has been awarded over 150 national and local awards for design excellence, which include: 19 Home of the Year awards, 7 Community of The Year awards, and recognized as the Homebuilder of the Year by the National Association of Homebuilders (NAHB), and numerous other awards.

Our Purpose



Enhancing lives by creating innovative homes and communities that inspire and reflect the unique interests of our residents. How we do anything is how we do everything. We are creators. The foundation of our success is rooted in our culture and our most valuable resource is our people. We are a diverse group made up of smart, creative, and dedicated people that are passionate about transforming the modern living experience.

Position Overview

The AI & Business Systems Manager is a senior, hands-on role responsible for designing, governing, and operationalizing artificial intelligence across Christopher Homes’ real estate development and luxury homebuilding platform. The manager will report to our CFO. This role requires deep, proven experience in real estate development and residential construction combined with advanced applied AI, data, and enterprise systems expertise.

The manager can work on-site or have a hybrid schedule.

This individual will lead the transformation of fragmented data and disconnected systems into a clean, structured, AI-ready ecosystem that improves efficiency, reduces costs, enhances forecasting, and elevates the customer experience. This is not a research role—this position focuses on practical, secure, ROI-driven AI embedded directly into daily workflows.

This is a full-time, individual contributor role with enterprise-wide responsibility and visibility.

Key Responsibilities

AI STRATEGY & IMPLEMENTATION (PRIMARY FOCUS)

·      Design and execute an enterprise AI roadmap aligned with real estate development and homebuilding workflows

·      Embed AI directly into core systems including Procore, ERP, Buildtopia, HubSpot, and Microsoft platforms

·      Identify and deploy AI use cases for:

–        Cost control and variance detection

–        Schedule and cycle-time optimization

–        Purchasing and vendor analysis

–        Warranty trend prediction and root-cause analysis

–        Marketing performance and lead intelligence

·      Automate repetitive, manual, and error-prone processes using AI and intelligent workflows

·      Ensure all AI solutions are secure, compliant, and aligned with data privacy best practices

DATA ARCHITECTURE, CLEANUP & GOVERNANCE

·      Assess, clean, normalize, and structure data across all business systems

·      Establish data standards, naming conventions, and governance policies

·      Eliminate duplication, silos, and inconsistent data definitions

·      Ensure data integrity to support reliable AI-driven insights and decision-making

·      Prepare data architecture to support future scalability and AI maturity

REAL ESTATE DEVELOPMENT & CONSTRUCTION SYSTEMS LEADERSHIP

Serve as the internal expert on how AI supports:

              – Land development

            – Vertical construction

-- Purchasing and contracts

            – Design center operations

            – Warranty and post-close service

·      Deeply understand how data flows through real estate development and homebuilding lifecycles

·      Optimize system usage to reflect how the business actually operates—not generic software assumptions

·      Partner with vendors, consultants, and software providers during system enhancements or ERP transitions

BUSINESS PARTNERSHIP & CHANGE MANAGEMENT

·      Translate real estate development and construction challenges into AI-enabled solutions

·      Partner closely with executive leadership and department heads

·      Educate teams on AI tools, best practices, and responsible usage

·      Adoption of AI-enabled workflows across the organization

REPORTING, FORECASTING & DECISION INTELLIGENCE

·      Build AI-powered dashboards, reports, and forecasting tools

·      Improve visibility into costs, schedules, risks, and performance

·      Enable leadership to make faster, more accurate, data-driven decisions

REQUIRED QUALIFICATIONS   

·      8+ years of experience in real estate development, residential construction, or homebuilding environments

·      Demonstrated, hands-on experience applying AI to real business systems

·      Deep understanding of development and construction workflows, terminology, and financial drivers

·      Proven ability to organize, clean, and govern complex operational and financial data

·      Experience with enterprise systems such as:

            – Procore

            – ERP systems (Sage 100 Contractor or similar)

             – Buildtopia (Purchasing, Design Center, Construction and Warranty)

            – CRM & Marketing platforms

            – Microsoft ecosystem (including Copilot)

·      Strong understanding of data security, privacy, and compliance in business environments

·      Ability to operate independently and drive outcomes without direct supervision

STRONGLY PREFERRED

·      Luxury single-family or for-rent residential development experience

·      Experience leading ERP transitions or system integrations

·      Applied knowledge of predictive analytics and automation in construction

·      Ability to communicate complex technical concepts to non-technical stakeholders

IDEAL CANDIDATE PROFILE

·      Deeply grounded in real estate development and construction

·      Business-first mindset with strong technical execution

·      Focused on measurable ROI, efficiency, and cost savings

·      Disciplined, pragmatic, and trustworthy with sensitive data

·      Comfortable building foundational systems before scaling AI initiatives

Join Our Mission to Bridge the Digital Divide - Through AI!

Position: Programs Manager (AI Curriculum - Higher Ed) - Austin, Texas (Hybrid or Remote)

Salary Range: USD 55,000 - 75,000 annually (with a 3-month probation)

Location: Preference for Austin, Texas; remote possible

Travel: Occasional travel required with reasonable notice and accommodations

About Us

Sustainable Living Lab USA (SLL LLC USA) is part of a global movement, HQ in Singapore, offices in India, Indonesia, Japan, and the USA, to make technology inclusive, accessible, and sustainable. We design and deliver innovative education programs that equip learners with essential digital and AI skills - from US community colleges to grassroots organizations worldwide.

About the Role

We’re seeking a dynamic, articulate, and adaptable Programs Manager (AI Curriculum for HigherEd)to support the global expansion and US localization of our AI education programs.

This role involves delivery, curriculum creation, and program development, ideal for someone confident in discussing AI with non-technical audiences, passionate about learning, and eager to influence AI upskilling’s future. You’ll lead technical Train-the-Trainer (TTT) sessions with professors from community colleges and universities both virtually and in-person helping them develop/integrate technical AI concepts as part of their certifications/degrees.

This role blends delivery, curriculum design, and program development, ideal for a flexible, self-motivated individual with a growth mindset who thrives in ambiguous environments, constantly finding solutions to new problems.

Key Responsibilities

1. AI Programs Training & Facilitation (TTT Model)

• Lead virtual and in-person technical Train-the-Trainer (TTT) workshops across US, supporting partners in vocational education and workforce institutions worldwide.
• Ensure participants understand the content and are equipped to customize it for local contexts and learner needs.
• Develop and implement standardized training regimens and SOPs tailored for cross-cultural, regional, and state-wide implementation partners.
• Translate core AI, ML, DL, and Python concepts into engaging, beginner-friendly lessons sensitive to language diversity and digital fluency levels - but also able to deliver technical concepts like Maths for AI, Data science, and Agentic AI topics in depth.
• Conduct engaging and informative training sessions utilizing a standardized curriculum.

2. US Programme & Business Development (SMEs, Colleges, Universities, K12, communities)

• Manage the continuity and expansion of SLL's US programs, particularly within its extensive network of 140+ community colleges and universities spanning 40+ states.
• Work with the team to position SL2 as a leading partner in AI and emerging tech education for the US community college and vocational sector.
• Scale educational programs with school districts, community colleges, and universities, focusing on out-of-school programs and boot camps.
• Scale AI Community Engagements with clubs, societies, and foundations.
• Identify and articulate compelling use-case stories for workforce development partnerships.
• Support engagements with colleges, government agencies, and employers to co-develop bespoke AI education pathways.

3. Content Development and Productization

• Collaborate with internal teams to evolve and update existing programs and co-create new offerings.
• Lead the creation of slide decks, training decks, and other content as a core part of the role.
• Contribute to productizing key experiential learning offerings such as hands-on coding challenges and platform-based simulated work experiences.
• Help localize material for US-based institutions, aligning with skills frameworks and employer demand.
• Co-deliver experiential coding/skilling events, ensuring the core product is designed for global scalability and is adaptable to various educational levels, including tailoring project focus for different competitions for community college and university students.

What We're Looking For

• HigherEd/SME Training Experience: Minimum of 3 years in Higher Ed, training, or facilitation working with HigherEd/SMEs, including at least 2 years focused on technical or digital skills. Experience working across cultures and time zones is highly valued.
• Tech & Learning Aptitude: Intermediate to high knowledge of Python and AI/ML/DL/Agentic AI/Maths for AI/Data concepts. Strong personal interest in the evolving AI landscape and comfort with explaining complex topics to beginners. Experience or enthusiasm for Vibe Coding, digital hackathons, or collaborative prototyping is a plus.
• Communication & Facilitation: Fluent, clear-spoken English and strong public speaking skills. Able to adjust tone, pace, and clarity based on audience (e.g., teachers vs. college professors vs. workforce leaders). A strong presence on MS Teams/Zoom or in person - whether running a classroom session, hackathon, or partner presentation.
• Mindset & Tools: Adaptable, self-motivated, and collaborative. Skilled in using tools like Zoom, Google Workspace, and Teams, and eager to learn new platforms and facilitation techniques.
• Location & Eligibility: Preference for candidates based in Austin, TX, but open to strong remote applicants. Must be authorized to work in the US.

Why Join Us?

• Make Global Impact: Empower teachers and workforce educators across continents to teach AI confidently and contextually.
• Shape the Future of the US Workforce Skilling: Co-create impactful AI programmes for colleges and workforce partners across the US.
• Creative & Collaborative Culture: Work with a mission-driven team that values experimentation, equity, and lifelong learning.
• Featured Benefits: Medical insurance (100% employer contribution), 14 days annual leave, 14 days medical leave, and paternity and maternity leave. We request that the candidate to have their own device.

Ready to Apply?

Send your resume and a short, authentic cover letter to with the subject line: “Programs Manager (AI Curriculum) - U.S.” Please write authentically, and use AI tools with discernment.

Please include:

• Your expected monthly salary in USD
• Your current location and time zone
• Your availability to start
• Any accommodation requests (if applicable)

SLL LLC USA is an Equal Opportunity Employer. We celebrate diversity and are committed to building an inclusive workplace. If you need accommodations during the application process, please let us know.

** We will only consider applicants who are currently residing in South Florida**

About MMG

MMG Equity Partners is a Miami-based, family-led real estate investment and development platform with a portfolio of retail shopping centers across South Florida. Beyond the real estate business, MMG operates a private family office that manages investments, insurance, and financial reporting across multiple entities and family members. MMG separately owns Tamarack Resort in Idaho. We are a flat, fast-moving organization where you will work directly with principals — not layers of management.

This is a ground-floor role. We are building the function from scratch. The right person will define what AI means at MMG, then build it.

The Role

The Director of AI Initiatives & Adoption is responsible for identifying, implementing, and managing AI tools and systems that meaningfully improve how MMG operates across real estate and family office functions. Every project you take on must connect to a business outcome — faster decisions, better data, more deals, reduced overhead.

You will own four things: identifying where AI creates real value at MMG, building or procuring the tools to capture that value, driving adoption across the team and continuously improving how those tools are used, and ensuring the systems are secure and maintainable. Implementation without adoption is not success.

• Reports to Managing Director
• Direct reports - contractors and freelancers as needed
• Current IT Enviroment - outsourced IT for network support

Current Tech Stack (what you are walking into)

You need to understand these systems deeply. Part of your job is figuring out how to connect them and leverage AI to make us more productive/competitive

What you will work on

Below are four areas where we believe AI creates the nearest near-term value at MMG. You first job is to work with the leaders in each area to assess each, prioritize, and build a 6-month roadmap. In addition to the below, the right individual will identify a myriad of other AI use cases to add value and reduce repetitive tasks.

1. Leasing and Tenant Prospecting

MMG owns retail shopping centers and is responsible for filling vacancies with the right tenants – while we work with third party leasing firms, we wish to supplement their efforts by generating direct leads.

• Design and build AI scraping tools to compile databases of South Florida retailers and service businesses for targeted uses
• Build a tool to identify prospective uses/tenants: given a vacancy (size, location, co-tenancy, demographics), which business types and specific operators are the best candidates?
• Design and build AI-assisted leasing outreach workflow: targeted uses identified for vacancies → database queried → outreach drafted and sent → responses tracked in Dynamics (or other CRM)
• Activate Microsoft Dynamics (or other) as the CRM for online leasing
• Identify tools or workflows to monitor existing tenant health (sales reporting, foot traffic, business review signals) to get ahead of vacancies before they happen
• Identify and implement AI-assisted lease abstracting tool to best fit our environment

2. Real Estate Acquisitions

MMG evaluates potential acquisitions across South Florida. Today this process is manual and dependent on individual knowledge. AI can accelerate every stage.

• Design and build AI scraping tools to compile databases of South Florida real estate owners
• Build an AI-assisted underwriting workflow that pulls property data, comps, and market context into a structured analysis template
• Identify AI tools for market intelligence — rent growth trends, cap rate movements, retail category performance by submarket
• Evaluate AI-powered deal sourcing tools (e.g. CoStar integrations, off-market sourcing platforms

3. Private Family Office

MMG's family office manages investments, insurance, and financial reporting for family members. This is a sensitive area requiring strict data governance — but it also has high-value AI applications.

• Addepar AI integration: explore ways to use AI to generate plain-language investment performance summaries and financial reports from Addepar data, reducing manual reporting time
• Insurance management: build a structured database or AI assistant for tracking insurance policies (G/L, personal property, family member policies) with renewal alerts and coverage gap analysis
• Document intelligence: connect family office files in SharePoint to an AI interface for on-demand retrieval of partnership agreements, tax documents, and legal filings
• Evaluate data governance and access controls for family office data — this is sensitive personal and financial information; AI access must be role-based and audited

IT Infrastructure and Security

You are not a network administrator — we have an outsourced IT firm for that. But you are responsible for AI governance at MMG: ensuring every AI tool introduced into the environment meets a clear security and accountability standard.  Practically, this means:

• Evaluating AI vendors for data handling practices — what data leaves our environment, where it is stored, and how it is used for model training
• Defining and enforcing a data classification policy: what information can be sent to external AI APIs, what must stay on-premise or in private cloud environments
• Working with IT firm to ensure AI tools are deployed within the MS365/Azure security perimeter where possible
• Evaluating the Claude Teams → Claude Enterprise migration and the Microsoft Connector configuration for SharePoint access — specifically, controlling which documents are accessible to AI and by which users
• Vetting any third-party AI integrations (i.e. ZoomInfo, Yardi, etc.) for compliance with firm data policies

Prompt Library & AI Adoption

Building the tools is only half the job. The other half is making sure the team actually uses them — and uses them well. This requires two ongoing responsibilities that most AI roles underestimate.

Prompt Library

You will build and maintain a living prompt library — a curated set of tested, optimized prompts for every recurring AI task at MMG. Examples include: underwriting analysis from a rent roll, lease abstraction for a specific clause type, tenant outreach drafts by use category, and insurance renewal gap analysis. The library lives in SharePoint, is accessible to the full team, and is updated continuously based on user feedback and evolving business needs. A well-maintained prompt library is what turns AI from a tool that one person uses well into a capability that the whole organization depends on.

Adoption Monitoring & Continuous Improvement

You are responsible for whether AI tools actually get used — not just whether they get deployed. This means tracking adoption across the team, identifying where workflows are not sticking, providing training and troubleshooting support to staff using AI tools, and iterating on both the tools and the prompts based on real usage patterns. You will serve as the primary internal resource for the team when they hit limitations or need guidance on how to get better outputs. Deployment without adoption is a sunk cost.

What we are looking for

Required:

• 3–6 years of experience in data, technology, or AI — ideally in a context where you had to figure things out without a large team around you
• Hands-on experience with AI tools and LLM platforms — not just using them, but building workflows, prompts, and integrations on top of them
• Demonstrated ability to connect AI capabilities to specific business outcomes (not just technology for its own sake)
• Comfort with the Microsoft 365 ecosystem — SharePoint, Dynamics, Teams, Azure
• Ability to manage and direct contractors and developers without being the one writing all the code
• Non-technical stakeholder communication — you will regularly present AI recommendations, tool evaluations, and implementation roadmaps directly to the principal(s) who are real estate operators, not technologists. The ability to translate AI capabilities into business outcomes (not feature lists) is non-negotiable. If you cannot explain why a tool matters in terms of time saved, deals sourced, or risk avoided, you will not be effective in this role
• In-office presence at Pinecrest HQ is required initially (possible hybrid in the future)

Preferred

• Experience in commercial real estate, property management, or a related field
• Familiarity with Yardi, Addepar, or similar platforms
• Background that includes both technical work (building things) and strategic work (recommending what to build)
• Experience implementing AI in a small-team / resource-constrained environment