This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client's time zone.
Client Overview
Our client is a B2B advisory business that works with confidential client, buyer, and transaction-related information. The company is looking to develop internal AI-powered tools and automations to improve research, buyer evaluation, internal briefings, and operational workflows.
Role Overview
The AI Automation Engineer will design, build, deploy, and maintain AI-powered internal tools that automate research, buyer evaluation, briefing preparation, and other business workflows.
Location
Fully Remote | 9:00 AM - 5:00 PM EST
Key Responsibilities
AI Application Development & Workflow Automation
- Design, build, test, deploy, and maintain AI-powered internal applications, automations, and workflow integrations.
- Translate business use cases into technical specifications and implementation plans in collaboration with leadership.
- Recommend technical approaches, identify implementation considerations, and refine solutions as requirements evolve.
- Use Claude Code, ChatGPT/Codex, and similar agentic development environments to build, troubleshoot, and improve applications.
- Evaluate and recommend AI models, development tools, and implementation approaches based on business requirements.
Buyer Research & AI-Powered Evaluation
- Develop workflows that combine client and listing information, market data, and structured research to identify potential buyers and strategic acquirers.
- Build systems that generate structured target lists for internal review and verification.
- Create AI-assisted buyer evaluation workflows using call transcripts, buyer information, internal scoring criteria, and leadership input.
- Develop automated processes for generating buyer scorecards, deal-team briefings, and seller-facing buyer summaries.
- Incorporate human-in-the-loop review processes to ensure AI-generated outputs are verified before external use.
API Integrations & Data Architecture
- Integrate internal tools with Fireflies, Streak CRM, Google Workspace, internal documents, APIs, and other approved platforms.
- Build and maintain APIs, databases, data pipelines, and backend systems supporting AI-powered workflows.
- Develop user-facing internal applications with intuitive interfaces that support adoption by non-technical users.
- Recommend appropriate development stacks, data architectures, AI models, and deployment approaches.
- Maintain reliable data exchange between connected applications and internal workflows.
Quality Assurance, Testing & Maintenance
- Develop test plans based on technical specifications and business requirements.
- Validate AI workflows, applications, and integrations through end-to-end testing.
- Identify and troubleshoot technical issues, workflow failures, and edge cases.
- Ensure internal tools function reliably before deployment and team adoption.
- Maintain existing applications and improve functionality as business requirements evolve.
Data Security & Stakeholder Collaboration
- Apply appropriate data security, access permissions, and confidentiality standards when handling sensitive business information.
- Collaborate with leadership to understand operational challenges and identify opportunities for AI automation.
- Communicate technical recommendations, implementation tradeoffs, progress, and requirements to non-technical stakeholders.
- Document technical decisions, workflows, maintenance requirements, and future development priorities.
Qualifications
Experience
- Proven experience building AI-enabled applications, workflow automations, internal tools, or agentic systems beyond basic chatbot implementations.
- Strong hands-on experience using Claude Code, ChatGPT/Codex, or similar AI coding environments to develop and improve working applications.
- Solid software development experience using Python, JavaScript/TypeScript, or a comparable programming language.
- Experience working with LLM APIs, structured outputs, prompt orchestration, and AI workflow design.
- Experience developing APIs, integrations, data pipelines, and database-backed applications.
- Experience integrating third-party SaaS platforms using APIs, webhooks, and automated workflows.
- Experience independently executing technical projects while collaborating with non-technical stakeholders.
- Ability to demonstrate previous AI implementations, including architecture, technical decisions, tradeoffs, and measurable outcomes.
- Experience handling sensitive, confidential, or business-critical information.
Skills
- Strong ability to use AI-assisted coding environments while independently evaluating, troubleshooting, and maintaining generated code.
- Ability to translate business problems into technical requirements, implementation plans, and functional applications.
- Strong understanding of AI workflow architecture, LLM integration, structured outputs, and prompt orchestration.
- Ability to develop and maintain APIs, database-backed applications, and automated data pipelines.
- Ability to integrate third-party platforms through APIs, webhooks, and workflow automations.
- Ability to recommend suitable AI models, development technologies, data architectures, and deployment approaches.
- Experience developing testing procedures, validating integrations, and troubleshooting technical issues.
- Ability to implement human-review processes for AI-generated outputs.
- Strong understanding of data security, confidentiality, and access permissions.
- Ability to develop intuitive internal tools for non-technical users.
- Ability to communicate technical decisions and implementation tradeoffs to business stakeholders.
- Ability to independently manage development responsibilities while adapting to evolving requirements.
Preferred Experience & Skills
- Experience with OpenAI, Anthropic/Claude, LangChain, LlamaIndex, n8n, Make, Zapier, Supabase, PostgreSQL, AWS, GCP, or similar technologies.
- Experience with call-transcript analysis, scoring models, structured reporting, or human-review workflows.
- Experience building internal CRM, research, sales-operations, or data-enrichment tools.
- Experience working in financial services, professional services, M&A, legal, or other industries handling confidential client information.
- Experience developing custom dashboards or lightweight internal web applications.
- Experience working with data-enrichment platforms, public-data sources, and company or contact research workflows.
Technical Environment
The Current Environment Includes
- Streak CRM: CRM and workflow management within Gmail.
- Google Workspace: Gmail, Google Sheets, Google Docs, and Google Drive.
- Fireflies: Call recording and transcript generation.
- ChatGPT and other AI tools: Internal research, drafting, and analysis.
What Success Looks Like
First 30 Days
- Develop a clear understanding of existing research, buyer-evaluation, and briefing workflows.
- Identify required data sources, integrations, security considerations, and technical dependencies.
- Present a practical AI automation roadmap outlining recommended architecture and implementation priorities.
- Begin developing an initial prototype or integration for the highest-priority business use case.
Opportunity
The AI Automation Engineer will have the opportunity to build internal AI-powered applications and automations that directly improve research, buyer evaluation, and operational processes within a B2B advisory business.