Summary We are looking for a Full Stack .NET Developer with experience in .NET, CSS, Javascript, Bootstrap 3 & 5, and React frameworks for project specific work. We are looking to convert pages from Bootstrap 3 to Bootstrap 5. If you are comfortable working in new modern .NET and legacy .NET Framework, while moving quickly from idea, design, and to working code, know how to leverage AI tools as a force multiplier (not a crutch), and enjoy building SOLID, clean, maintainable systems end-to-end, we would like to hear from you. Professional Qualifications: ASP.NET MVC, .NET, C#, React, Javascript, jQuery, HTML/CSS, Bootstrap 3 & 5 migrations, Azure, DevOps. Leverage AI as a productivity multiplier to solve business problems and improve internal processes. Solid problem-solving and debugging skills, with the ability to tackle more complex and ambiguous issues. Proficiency in software development best practices, including SOLID principles, design patterns, and testing strategies. Experience designing, developing, and maintaining end-to-end features or services of moderate complexity. Familiarity with system architecture concepts and ability to articulate trade-offs. Prior experience mentoring peers and sharing knowledge and best practices to strengthen team capabilities. Personal Qualifications: Strong ownership mindset with the ability to work independently on larger scopes. Proactive communicator who ensures alignment across team members and stakeholders. Demonstrates leadership qualities, including empathy, patience, and clarity when mentoring or reviewing code.

Time GIS Pipelines (ArcGIS GeoEvent, ETL) Overview: Seeking a senior, U.S.-based Data Integration Architect to design and build the real-time and batch pipelines feeding an enterprise ArcGIS digital twin for a large infrastructure/port program. Native Esri delivery. Scope: ArcGIS GeoEvent Server pipelines; AIS / port community system feeds; ERP (SAP / Yardi) connectors; ETL automation; sub-15-minute refresh on time-sensitive layers; integration governance and data dictionary. Required: AWS Solutions Architect; ArcGIS GeoEvent Server administration; Azure Data Engineer; proven real-time/API/ETL integration at enterprise scale; U.S.-based (mandatory — no offshore); To apply: list your AWS/Azure/GeoEvent certifications with dates, and link two real-time data-integration projects you personally architected.

# Principal AI Data Platform Architect ## Company Overview We are a fast-growing AI-native firm working with executives, operators, private-markets investors, and enterprise teams to redesign how mission-critical work gets done with AI. We move quickly, care deeply about execution quality, and build practical systems where data, workflows, and AI agents come together in production. Our work often sits inside complex enterprise environments with sensitive private data, messy documents, high-stakes decisions, and strict access controls. We are not building generic dashboards or chatbots. We are building governed operating systems that help people answer important business questions faster, with source trails and permission boundaries intact. ## Opportunity We are looking for a principal-level Data Platform Architect to design and build the governed data spine behind AI-native operating systems for private-markets and enterprise environments. This role is for a senior, hands-on builder who can architect the foundation and ship production-grade systems: ingestion, lakehouse layers, canonical entities, lineage, quality checks, permissions, semantic models, and serving APIs. Outstanding performers may be considered for expanded or longer-term opportunities, including deeper platform ownership. ## Scope of Work - Architect a lakehouse-style data platform across structured and unstructured enterprise sources. - Build ingestion pipelines from SharePoint, Microsoft 365, CRM systems, document repositories, spreadsheets, and financial or operational data feeds. - Design Bronze/Silver/Gold data layers with replayability, lineage, quality checks, and point-in-time correctness. - Create canonical entity models for companies, people, deals, documents, metrics, funds, assets, and relationships. - Implement role-based and attribute-level access controls at the data layer, not just the UI. - Build semantic models and APIs that downstream AI workflows can safely query. - Partner with AI engineers building RAG, extraction agents, and executive command surfaces. - Document architecture, tradeoffs, operating standards, and handoff paths clearly. ## Must-Haves - Expert Python, SQL, and modern data engineering. - Deep experience with Databricks, Snowflake, or comparable lakehouse/data-platform architecture. - Hands-on experience with dbt or comparable transformation frameworks. - Experience building governed enterprise data systems with lineage, quality tests, CI/CD, and observability. - Familiarity with Microsoft Graph, SharePoint, Microsoft 365, or similar enterprise content ingestion. - Experience with entity resolution, master data management, semantic layers, or canonical data modeling. - Strong judgment around sensitive data, access controls, auditability, and reliability. - Ability to personally architect and ship production systems, not just advise. ## Nice-to-Haves - Private equity, private markets, financial services, investment workflows, or enterprise knowledge-management data experience. - Experience with DealCloud, HubSpot, PitchBook, AlphaSense, S&P, fund admin feeds, or similar business-data sources. - Experience with graph databases, vector databases, or RAG-ready data architecture. - Azure, Entra ID, RBAC, row-level security, or regulated-data environments. - Experience turning a client-specific data platform into reusable product infrastructure. ## What We're Looking For in a Person We are looking for a serious enterprise data architect who cares about correctness, lineage, permissions, and reliability. The right person has built real systems with messy data and real users. They know that the hard part is not making a demo work; it is making the data trustworthy, traceable, secure, and useful every day. This person should be senior enough to challenge the architecture, hands-on enough to ship, and clear enough to explain technical tradeoffs to non-technical operators. ## Category **Data Science & Analytics - Data Engineering** ## Screening Questions 1. Describe a governed data platform, lakehouse, or enterprise data architecture you personally designed or built. What were the sources, layers, and serving use cases? 2. What is your hands-on experience with Databricks, Snowflake, Delta Lake, Iceberg, or comparable platforms? 3. Have you built entity-resolution, master-data, or canonical data-model systems? Describe the matching approach and human-review process. --- ## Skills - Data Engineering - Data Architecture - Databricks - Snowflake - SQL - Python - dbt - ETL Pipeline - Data Lake - Microsoft Azure - API Integration - Data Modeling - Data Warehousing - Lakehouse Architecture - Microsoft Graph - SharePoint Integration - Entity Resolution - Master Data Management - Semantic Layer - Data Lineage - RBAC - Private Equity Data

ePanicButton is an 18-year-old B2B SaaS real-time alert platform (Windows desktop client, React Native mobile app, admin portal, REST API), mid-way through a major modernization: portal rebuild, production server migration, and a shift toward AI-assisted development. We're a small, bootstrapped business — no VC funding, no big budget, and no room for enterprise-scale overhead. We need a senior engineer with real entrepreneurial experience — someone who's built or run their own thing and knows how to bring enterprise-grade discipline to a lean operation without over-engineering it. This is primarily a hands-off oversight role: the founder handles day-to-day setup and coding using AI tools (Claude, Claude Code), and you review the work, verify the high-risk items yourself, and weigh in on major architecture decisions. When something gets stuck — a deployment issue, a security question, an architecture call that matters — you're able to step in directly and get hands-on to unblock it. You'd effectively be the technical boss: the founder builds day-to-day, and you set standards, review and verify the work, and own final say on the platform's operational integrity — all in a way that fits a small company's budget and pace. ## Priorities, In Order **1. Secure and stabilize the program.** Get infrastructure, credentials, certificates, source control, and deployment process under real, enterprise-grade management so the platform runs effectively and reliably — no more surprises. **2. Establish AI-driven development and program management.** Build the process, guardrails, and review discipline for a workflow where the founder handles the actual AI-assisted coding, and you own the architecture decisions, code review, and release management around it. **3. Bittensor integration.** Help guide and oversee the buildout of our REST API messaging layer to serve the Bittensor decentralized AI mining/subnet community as a new channel-partner market. ## Core Responsibilities - Review infrastructure architecture, server management, backup, and disaster recovery decisions; personally verify high-risk items (credentials, DNS, prod access) rather than just reviewing notes about them - Oversee consolidation and hardening of credentials/secrets management; confirm it's actually done right, not just described as done - Confirm certificate lifecycle management is properly set up and tracked (SSL/TLS, renewals) - Set standards for GitHub structure, access control, branch strategy, and release process; step in directly if something gets stuck - Review and approve AI-generated code and architecture before it hits production; weigh in directly on major architecture decisions - Be available to get hands-on and unblock things — a stuck deployment, a security question, an architecture call that matters — even though day-to-day execution isn't the default expectation - Mentor the founder as a working AI-assisted developer; coordinate outside contractors toward one architecture - Weigh in on strategy for the Bittensor/API-partner buildout once the foundation is secure ## What We're Looking For - Senior engineer (CTO, VP Eng, Head of Infrastructure, or equivalent) with real production ownership at scale - Entrepreneurial background — has run or built something of their own, not just managed inside someone else's org - Comfortable working with a small, bootstrapped company's budget and pace — pragmatic about scope, not looking to build enterprise overhead we can't afford - Primarily comfortable in a review/oversight capacity, but able and willing to get hands-on directly when something is stuck or a decision is high-stakes enough to warrant it - Comfortable with server/cloud infrastructure, DNS, certificates, and secrets management discipline - .NET/SQL Server background (our stack); ASP.NET Core, SignalR, Azure/Windows Server a plus - Real current experience working alongside AI coding tools — comfortable reviewing and directing AI-assisted dev, not just aware of it - Strong communicator who can explain technical risk clearly to a non-developer founder **Nice to have:** B2B SaaS / white-label / multi-tenant experience, real-time notification systems, familiarity with Bittensor or decentralized AI/Web3 ecosystems, prior fractional CTO experience with founder-led companies. ## How We Work This is a genuine partnership for our next stage of growth, not a one-off audit — we're securing the platform's foundation, then building out the AI-driven development process, then expanding into the Bittensor/API-partner market. Expect close communication, real decision-making authority, and someone who wants to grow into this alongside us.

About Us We are an AI-powered healthcare platform delivering affordable, on-demand virtual care through modern cloud infrastructure and intelligent automation. As we prepare for launch and scale, we’re looking for a hands-on Azure Security & Infrastructure Architect to strengthen, secure, and operationalize our Azure environment. This is not a purely advisory role. We need someone who can step into a fast-moving startup environment, assess infrastructure and security risk quickly, implement practical controls, improve environment governance, and help establish a stable operational foundation for a healthcare platform handling sensitive data. Your mission: 👉 Make the Azure environment secure, controlled, scalable, and operationally predictable. About the Role This is a hands-on Azure architecture and security role focused on: infrastructure hardening environment governance access control operational security PHI-conscious infrastructure design Azure best practices You will work closely with leadership, developers, and DevOps resources to: identify and remediate security risks improve environment structure and governance reduce operational exposure implement practical controls appropriate for a healthcare platform This role is ideal for someone who understands how to balance: startup speed cloud security operational discipline practical execution Key Responsibilities Azure Infrastructure & Governance: Audit and rationalize Azure infrastructure across development, staging, and production environments Define and enforce clear environment separation standards Review and optimize: Virtual Machines (VMs) VM Scale Sets (VMSS) Networking Load balancers Application gateways Storage accounts Databases Eliminate infrastructure drift and undocumented system behavior Improve operational visibility and environment consistency Security & Access Control: Harden Azure environments using security best practices Review and secure: RBAC/IAM permissions Networking rules Public exposure risks SSH/server access Secrets management Environment access policies Implement practical security controls appropriate for a healthcare platform handling sensitive data/PHI Ensure environments are auditable, controlled, and operationally secure Support incident readiness and disaster recovery planning PHI-Conscious Security & Compliance: Help establish and validate security controls aligned with HIPAA-conscious operational practices Identify infrastructure-level risks related to: PHI exposure logging practices access management environment segregation data protection Partner with engineering leadership to reduce security and compliance risk without slowing development unnecessarily Assist with infrastructure documentation and operational security standards Infrastructure Cleanup & Optimization: Audit and identify: duplicate resources unused infrastructure legacy/test environments unnecessary cloud spend Safely simplify and consolidate environments where appropriate Recommend practical improvements for scalability, resilience, and operational maturity Required Experience: 7+ years in cloud infrastructure, Azure architecture, cloud security, or platform engineering roles Deep hands-on Microsoft Azure experience Strong expertise in: Azure networking, RBAC/IAM, VMSS, Application Gateways / Load Balancers, Azure security best practices, Infrastructure governance, Secrets management, Infrastructure hardening Experience securing production cloud environments Strong understanding of: healthcare or regulated-environment security considerations, environment isolation, operational controls, access management, disaster recovery planning Comfortable operating hands-on inside Azure environments, not just advising teams Experience cleaning up or stabilizing fast-grown startup environments Nice to Have: Healthcare, HIPAA, or regulated-industry experience Experience supporting pre-launch or scaling startup platforms Cloudflare/WAF/security tooling experience Docker/containerization familiarity Laravel/PHP or Next.js infrastructure familiarity Ideal Candidate: Hands-on operator, not just strategist Security-minded without becoming a bottleneck Able to identify practical risk vs theoretical risk Strong communicator who can explain technical decisions clearly Comfortable bringing order to environments that evolved quickly Thinker and doer with strong ownership mentality

AZURE DEPLOYMENT SPECIALIST - LONG-TERM PARTNERSHIP OPPORTUNITY ** READ ATTACHED DOCUMENT FOR COMPLETE DETAILS ** ABOUT US: Symeron Software - 20+ years serving 6,000 automotive dealerships. Expanding our AI-powered platform using Azure AI services. Need reliable Azure deployment partner for ongoing work. FIRST PROJECT (FIXED-PRICE): Deploy 3 completed applications to Azure production: 1. Document scanner - Node.js, Azure Blob Storage, Cognitive Services OCR, Azure SQL 2. Sales pipeline - HTML/JS frontend, Node.js backend, email processing 3. CRM integration tools DELIVERABLES: ✓ Deploy all 3 apps to our Azure production account ✓ Configure production security ✓ Set up Azure Monitor & Application Insights (standard Azure only) ✓ Documentation for day-to-day management ✓ 1-hour handoff/training call ONGOING WORK POTENTIAL: This is the FIRST of 5-6 projects over next few weeks, with potential monthly ongoing work. We're looking for long-term partnership - someone who becomes our go-to Azure expert as we scale to 6,000 customers. WHAT WE VALUE MOST: 1. RELIABILITY - Does what you say, meets deadlines 2. COMMUNICATION - Same-day responses, clear explanations (CRITICAL - previous freelancers failed here) 3. SKILL SET - Real Azure production experience + Azure AI knowledge 4. AVAILABILITY - Want long-term relationship, not one-off contractor REQUIRED: ✓ Azure Administrator (AZ-104) or Solutions Architect (AZ-305) certified ✓ 5+ years Azure production deployment experience ✓ Azure AI/Cognitive Services experience ✓ US-based or native English speaker ✓ Excellent communication skills ✓ Available to start within 48 hours ✓ Interested in ongoing work BUDGET: Fixed-price (provide your quote) TO APPLY - MUST INCLUDE: 1. Azure certifications 2. Recent Azure production deployment example 3. Azure AI/Cognitive Services experience 4. YOUR FIXED-PRICE QUOTE for complete project 5. Confirmation you want long-term work 6. Typical response time for messages NOT LOOKING FOR: ✗ MSPs or managed services companies ✗ Agencies (individual consultants only) ✗ Proprietary monitoring platforms ✗ Code rewrites (apps are built and working) ** IMPORTANT: See attached PDF for complete project details, company background, future work scope, and evaluation criteria ** TIMELINE: - Select partner this week - Start immediately - Complete deployment within 2 weeks - Begin next projects if successful We're ready to move fast with the right partner. Quality work on this project = ongoing relationship with established, growing company. Questions? Apply with required information and we'll schedule video call.

Looking for someone who can help consult in developing systems and applications leveraging Azure, M365, and LLMs/AI. Must be able to communicate well and have deep knowledge of the services and how to implement them.

We are a small software development team actively using Claude and GitHub Copilot for development on an ASP.NET and Azure technology stack. We’re looking for an experienced AI coach/consultant who can review how our team currently uses AI, identify opportunities for improvement, and help us work more effectively with Claude Code, agents, and AI-assisted development workflows. What we're looking for: Experience implementing and scaling AI-assisted development practices within agile software teams. Deep hands-on experience with Claude Code, agents, and agent-driven workflows. Experience designing and configuring agents for development, QA, testing, documentation, and other engineering processes. Ability to conduct team workshops, coaching sessions, and practical reviews of our current workflows. Strong understanding of software engineering best practices, not just AI tooling. Bonus skills: Software architecture and platform engineering experience. Experience setting up and optimizing MCPs (Model Context Protocol), tools, integrations, and custom Claude configurations. Knowledge of AI workflows beyond development, including QA, support, project management, and internal operations. The engagement would likely include a mix of: Reviewing our current processes and tooling One-on-one discussions with team members Team coaching and training sessions Recommendations for improving productivity, quality, and collaboration using AI Please include examples of teams you have coached, AI development workflows you have implemented, and your experience with Claude agents and MCP-based tooling

We are looking for a hands-on Forward Deployed AI Engineer to help build practical AI systems This is not a pure backend role and not a strategy-only consulting role. You will work close to end users, understand how their workflows actually operate, and then build AI-enabled tools that solve specific business problems. The ideal person is a strong software engineer who is comfortable with ambiguity, can communicate clearly with non-technical stakeholders, and can take an AI prototype from idea to something reliable and usable. What you will do - Learn the business workflows, systems, data, and constraints. - Build AI applications using Claude or similar large language models. - Use the right mix of prompting, retrieval, tool use, agents, and workflow automation. - Own delivery from scoping through prototype, testing, hardening, and handoff. - Create evaluations to determine whether the system is accurate, reliable, and safe enough to use. - Translate between domain experts and technical implementation. - Work carefully with sensitive or regulated data. - Document what you build so it can be maintained and reused. What we are looking for - Strong Python engineering skills. - Hands-on experience building with LLMs, preferably Claude or the Anthropic API. - Experience with RAG, structured prompting, tool use, evaluation, or agentic workflows. - Ability to operate independently in a messy, ambiguous environment. - Strong communication skills with both technical and non-technical stakeholders. - Track record of shipping working software, not just demos. - Comfort working with real-world data, integrations, and imperfect requirements. Helpful but not required - Prior forward deployed engineering, solutions engineering, or technical consulting experience. - Experience building AI tools for enterprise customers. - Experience in regulated or sensitive-data environments. - Familiarity with validation, auditability, traceability, or compliance-oriented workflows.