Reports to: Chief of Staff
Location: Remote (U.S. time zones preferred) | Occasional onsite as needed
Company: C1M.ai (https://C1M.ai)
Role Summary
C1M.ai is seeking an AI Development Lead who blends delivery leadership, technical depth, and change management to accelerate how we build with AI. This leader is a proven project manager who can translate business needs into technical execution plans, manage multiple workstreams, and ensure high-quality outcomes across integrations, automations, data flows, and AI features.
In addition to leading delivery, you will drive a developer transformation program—standardizing how our teams use AI development tools (coding copilots, agentic workflows, automated testing/documentation, etc.) to improve speed, quality, and consistency. You’ll also help develop internal AI capabilities, including training and fine-tuning models on C1M.ai-approved patterns, templates, and reusable components.
Key Responsibilities
Delivery Leadership & Project Management
Own end-to-end delivery for AI and automation initiatives; ensure consistent execution standards.
Build and manage project plans, timelines, milestones, dependencies, and resourcing across concurrent initiatives.
Run agile ceremonies (backlog grooming, sprint planning, daily standups, retros) and maintain delivery metrics.
Identify risks early, remove blockers, and communicate status clearly to stakeholders (including the Chief of Staff).
Ensure requirements are captured, scoped, estimated, and delivered with high quality and minimal rework.
Technical Oversight (Hands-On Leadership)
Provide technical direction across:
Automation & integration: n8n, Zapier (webhooks, triggers/actions, API integrations)
Custom development: Python services, API development, data processing, and AI orchestration
Cloud: AWS and Microsoft/Azure where applicable; secure deployment patterns and operational readiness
Microsoft AI ecosystem: Azure AI services, OpenAI integrations, Microsoft 365/Copilot-related development patterns
Review and improve architecture decisions for reliability, maintainability, and scalability.
Establish “definition of done,” delivery standards, and integration patterns that are consistently applied.
Developer Transformation Using AI Tools
Lead adoption of AI-enabled development practices across the organization (copilots, code review assistants, test generation, documentation automation, agentic workflows).
Create a training and enablement program: onboarding, playbooks, office hours, internal demos, and certification of best practices.
Define and track measurable outcomes (cycle time, defects, rework, throughput, delivery predictability).
Implement guardrails for secure and responsible use of AI tools (IP protection, client confidentiality, data handling, prompt hygiene).
Internal AI Patterns & Model Enablement
Curate and standardize C1M.ai design patterns: integration templates, orchestration patterns, error handling, retries, logging/monitoring, security defaults, and documentation conventions.
Build and maintain a pattern library (docs + code/flow templates) that accelerates repeatable delivery.
Support internal model development efforts, including training and fine-tuning models on approved design patterns, templates, and internal standards—ensuring compliance with privacy, security, and licensing requirements.
Quality, Documentation, and Governance
Implement QA practices across automation and code (testing strategy, regression checks, monitoring, error handling).
Standardize documentation: architecture notes, runbooks, integration maps, and handoff materials.
Improve operational stability: logging, alerting, retries, incident response processes, and postmortem discipline.
Coordinate with stakeholders on acceptance criteria and change management.
People Leadership
Lead, mentor, and coach developers/builders; foster accountability and continuous improvement.
Support hiring, onboarding, performance feedback, and skills development.
Build a culture of clarity: well-defined work intake, high-quality tickets, strong communication, and predictable delivery.
Required Qualifications
5+ years leading technical delivery and/or serving as a technical project lead in software/integration environments.
Demonstrated success managing multiple projects simultaneously (timeline, scope, stakeholder management, delivery reporting).
Strong understanding of APIs, authentication (OAuth, API keys), webhooks, data formats (JSON/CSV), and integration patterns.
Practical experience with n8n and/or Zapier, plus Python and AWS, and exposure to Azure/Microsoft AI stack.
Hands-on experience implementing or integrating LLM/GenAI solutions in real business workflows.
Experience driving adoption of new tools/processes across engineering teams (enablement + measurement).
Excellent written and verbal communication—able to explain complex systems simply.
Preferred Qualifications
Experience with: Azure OpenAI, Azure Functions, Logic Apps, Power Platform, MS Graph, or Microsoft 365 integrations.
Experience building internal developer platforms, reusable accelerators, or pattern libraries.
Familiarity with model training/fine-tuning workflows, evaluation, and governance (e.g., data curation, prompt libraries, eval harnesses).
Familiarity with RAG, embeddings, vector databases, and agent orchestration patterns.
Experience in a professional services environment delivering for external clients.
Certifications (nice-to-have): PMP, Scrum, AWS, Azure, or relevant automation platform credentials.
What Success Looks Like (First 90 Days)
Establishes a predictable delivery rhythm (intake → estimation → execution → reporting).
Launches an AI developer enablement program with playbooks, training sessions, and measurable adoption.
Implements shared standards for documentation, QA, monitoring, and handoffs.
Publishes a v1 “C1M.ai Pattern Library” with reusable templates for common integrations and AI workflows.
Demonstrably improves throughput and reduces rework via AI-assisted development practices.
Core Skills & Traits
Builder-leader mindset: hands-on enough to guide architecture and unblock teams.
Strong operator: organized, disciplined, and metrics-driven.
Change agent: can drive adoption, build momentum, and manage resistance constructively.
Client-first: balances speed with quality and focuses on business outcomes.
High integrity with security, confidentiality, and responsible AI practices.
How to Apply
Send resume + a short note describing:
A project where you led both technical execution and project management,
An automation/integration you’re proud of (n8n/Zapier/API), and
How you’ve driven AI tool adoption or built internal standards/templates for teams.
