Job Description

Fully remote, reporting to leadership at Alaris Acquisitions

**About the Role**
You'll partner directly with leadership and our M&A deal teams as the embedded
AI engineer responsible for designing, deploying, and continuously improving
AI solutions that power our business. You will design, build, and maintain AI
powered agents that automate our M&A workflows. You will own the development &
maintenance within the AI v7 platform end to end, from agent architecture &
proof of concepts through go-live production deployments, working closely with
leadership and deal teams to turn heavy data processes into reliable,
auditable automation.

**Company Culture**
Alaris Acquisitions is a boutique sell side M&A advisory firm specializing in
the wealth management industry, helping sellers of Registered Investment
Advisors find the right buyers through a Deal Advocacy process built on
objective data and AI driven matching rather than traditional auctions. The
firm has completed over 100 acquisitions across 15 plus years with zero post
transaction breakups, guided by integrity, transparency, and long term
alignment over short term valuation.

**_Responsibilities_**

**AI Solution Development**
-Design and implement production grade AI agents using LLMs and agentic workflows within our AI platform.
-Build agents capable of reasoning, tool use, and multi step workflow automation across financial analysis, seller due diligence, buyer matching, and onboarding.
-Develop retrieval augmented generation (RAG) solutions connecting agents to firm knowledge and deal data.
-Design evaluation frameworks to measure agent accuracy, reliability, and output quality.
-Optimize prompts, orchestration logic, and inference performance.

**Software Engineering & Integration**
-Develop production quality logic in Python for agent workflows, data transformations, and custom automations.
-Build and maintain integrations using REST APIs, webhooks, and OAuth to connect the AI platform to CRMs, document repositories, and internal databases.
-Work with JSON for API payloads, agent configurations, and data interchange.
-Integrate v7 with tools such as Hubspot, Slack, Google Workspace, Microsoft 365, Webflow, Xano and other deal tracking systems as needed.

**Data & AI Operations**
-Design data ingestion and preprocessing pipelines for multi modal data, including PDFs, spreadsheets, and other documents.
-Build human in the loop review steps for critical agent outputs.
-Monitor agent performance in production, troubleshoot issues, and maintain clear documentation of agent logic and known issues.

**Stakeholder Engagement**
-Lead technical discovery with internal stakeholders and translate M&A workflow needs into agent designs.
-Communicate technical concepts clearly to non technical team members and leadership.

**Requirements**
-Strong Python development experience and comfort building production grade AI applications or agent based workflows.
-Experience with Large Language Models, agentic AI systems, and strong prompt engineering skills.
-Familiarity with retrieval augmented generation (RAG), tool calling, and AI evaluation frameworks.
-REST API development and integration experience, including webhooks and OAuth.
-Comfort with JSON based data structures.
-Familiarity with Git and modern software engineering practices.
-Strong communication skills and the ability to translate technical work into business value.

**What Success Looks Like**
-Co manage the AI platform from concept to production.
-Continuously identify opportunities to automate internal workflows.
-Deliver production-ready AI agents that are trusted by business users.
-Establish engineering standards, testing practices, and governance for future AI development.
-Serve as the technical expert for AI initiatives across the organization.