AI Automation Engineer

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.

The ideal candidate has a strong coding foundation and proven experience building functional AI applications using Claude Code, ChatGPT/Codex, or similar agentic development environments.

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.

The AI Automation Engineer will help determine the appropriate development stack, data architecture, AI models, and deployment approach as the internal automation roadmap evolves.

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.

Application Process:

To be considered for this role these steps need to be followed:

• Fill in the application form
• Record a video showcasing your skill sets