GTMM AI Solutions Engineer
Boston, MA, 02110
Apply now: GTM AI Solutions Engineer, location is Remote. The start date is ASAP for this 9-month contract position.
Job Title: GTM AI Solutions Engineer
Location-Type: Remote
Start Date Is: ASAP
Duration: 9 months
Compensation Range: $50-$55/hour W2
Benefits: Eligible for Health, Dental, Vision, 401K
Must be authorized to work in the U.S. This position is not eligible for sponsorship.
Job Description:
The GTM AI Solutions Engineer will design, build, deploy, and optimize AI-powered solutions that support Go-to-Market (GTM) teams. This individual will help develop AI assistants, automate workflows, connect enterprise systems, and transform complex business and technical information into accessible tools that improve team productivity and support operations.
Day-to-Day Responsibilities:
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Lead AI solutions from discovery and proof of concept through MVP development, testing, deployment, and launch.
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Take ownership of an existing AI-powered GTM support assistant and expand its capabilities.
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Build AI agents, assistants, retrieval systems (RAG), and knowledge libraries grounded in business and platform data.
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Develop automated workflows for support intake, ticket triage, routing, and notifications through Microsoft Teams.
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Build and deploy AI applications using Claude, Microsoft Copilot Studio, Python, and relevant AI APIs.
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Integrate enterprise platforms and systems using REST APIs, MCP connectors, and other integration methods.
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Evaluate AI models, frameworks, and data storage options while monitoring token consumption and operating costs.
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Implement security guardrails, role-based access, prompt-injection protection, and appropriate data-handling practices.
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Collaborate with business stakeholders and subject-matter experts to understand requirements and validate solutions.
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Rapidly prototype new AI tools, gather user feedback, and iterate toward production-ready applications.
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Deploy applications within Azure and Microsoft 365 environments.
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Monitor AI performance, usage, response quality, latency, and cost.
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Document architecture decisions, create technical runbooks, and ensure solutions can be supported by other teams.
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Identify additional opportunities to improve GTM workflows through AI automation.
Minimum Requirements:
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2 years of experience building software solutions, applications, or automation.
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At least 1 year of hands-on experience building LLM-based AI agents or assistants.
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Strong hands-on experience with Claude, Claude Code, or equivalent agentic coding tools.
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Experience working with Claude or OpenAI APIs.
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Proficiency in Python and REST API integrations.
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Understanding of Model Context Protocol (MCP), identity management, and role-based access controls.
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Experience building and deploying AI-powered applications or working prototypes.
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Understanding of LLM cost optimization, including model selection, prompt caching, context management, and token usage.
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Ability to translate complex technical concepts into solutions that nontechnical stakeholders can understand.
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Strong communication, problem-solving, and stakeholder management skills.
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Ability to work independently, manage multiple initiatives, and adapt quickly in a developing environment.
Preferred Qualifications:
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Experience with Microsoft Copilot Studio or Microsoft Bot Framework.
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Hands-on experience with Azure, including Azure App Service, Container Apps, Azure AI Foundry, Azure OpenAI, or Entra ID.
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Experience deploying AI applications or agents within Microsoft Teams.
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Experience integrating enterprise SaaS platforms such as Salesforce, Seismic, or ServiceNow.
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Background in Marketing, Sales, Revenue Operations, or GTM Systems.
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Experience with retrieval-augmented generation (RAG), knowledgebase development, and answer-quality evaluation.
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Familiarity with AI evaluation and tracing tools such as Langfuse, LangSmith, or Azure AI Foundry Evaluations.
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Understanding of LLM security risks, including prompt injection and data leakage.
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Experience with enterprise security reviews, user acceptance testing (UAT), and compliance requirements.
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Experience with Azure cost management, GitHub Actions, CI/CD, or infrastructure as code.
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Experience connecting multiple enterprise systems and building integrated workflows.
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