Applied AI Engineer (Due July 16th)

HqO•Boston, MA

3d•Onsite

About The Position

HqO is seeking an Applied AI Engineer to embed with their Operations and DevOps teams. This role will focus on identifying high-leverage problems, building production-grade AI agents and automations, and developing tools to enhance company effectiveness. The company is described as a fast-moving, 100-person organization that values high ownership and takes AI seriously. The ideal candidate is a builder with high agency, who moves with urgency and enjoys turning ambiguous problems into working systems.

Requirements

Demonstrated experience building something real with AI (e.g., a side project, automation, internal tool, or workflow used by others).
Comfort using AI-assisted coding tools (Claude, Cursor, Copilot) as a core part of the development process.
Working knowledge of Python and/or modern scripting and backend tooling.
Familiarity with LLM APIs, agentic patterns, and connecting systems via APIs and webhooks.
Ability to work on-site in Boston full-time.
High agency: ability to define problems, scope solutions, and drive them forward independently.
Does not require visa sponsorship.

Nice To Haves

Experience building agentic AI workflows (multi-step reasoning, tool use, orchestration, chaining).
Exposure to RAG systems, embeddings, or vector databases.
Experience integrating APIs or working across SaaS systems (HubSpot, Linear, Slack, Jira, or similar).
Familiarity with MCP modules or agent-to-agent communication frameworks.
Exposure to frontend or full-stack development.
Background in SaaS, PropTech, or B2B operations.
Computer Science degree (portfolio of shipped work is valued more).

Responsibilities

Identify and own high-leverage problems by embedding with Operations and DevOps teams to surface workflow inefficiencies and translate them into scoped, buildable solutions.
Own problems end-to-end, including discovery, design, build, deploy, and iteration.
Partner directly with team leads and the COO to prioritize work that improves speed, accuracy, and operational leverage.
Design and implement LLM-powered automations, agent workflows, and internal tools to reduce manual work and increase team capacity.
Build agentic systems that chain tasks, take actions, and integrate with HqO's internal stack (CRM, ticketing, infrastructure tooling, customer workflows).
Deploy MCP modules and agent-to-agent frameworks where they create genuine operational leverage.
Use AI-assisted coding tools to prototype rapidly, gather feedback, and iterate toward production-ready systems.
Own the rollout of shipped tools, drive adoption, and define success metrics.
Document built systems to ensure maintainability and extensibility.
Surface patterns from deployments to inform HqO's broader AI Operating Model and platform direction.
Help teams transition from basic AI usage to structured workflows, deeper integrations, and agent orchestration.
Extend HqO's existing foundation of over 15 deployed agents.
Contribute to a company culture that encourages experimentation and AI fluency.