Note: The job is a remote job and is open to candidates in USA. Enduring Ventures is a permanent capital holding company that acquires and grows businesses across multiple industries. The company is seeking an AI Forward Deployed Engineer to scope, build, deploy, and support AI solutions across its portfolio companies, automating workflows and delivering measurable business outcomes. The role is an individual contributor position that reports to the Chief Technology Officer and begins as a contract engagement with intent to convert to full-time.
Responsibilities
- Embed with portfolio company teams to understand their workflows, identify bottlenecks, and find the highest-value opportunities for AI
- Scope AI projects into well-defined deliverables with clear success metrics and positive business outcomes
- Build and deploy AI solutions end to end: prototype quickly, iterate with users, and harden solutions for production
- Design and build Claude skills, Claude harnesses, and agentic harnesses, as well as agents and workflows on other platforms
- Build and deploy agents, copilots, and automations in Microsoft Copilot, Copilot Studio, Microsoft Foundry (formerly Azure AI Foundry), and Amazon Bedrock / Bedrock AgentCore, meeting each portfolio company where its technology stack already lives
- Develop LLM-powered applications including RAG pipelines, tool-using agents, multi-step agentic workflows, and MCP/tool integrations
- Evaluate and select models across Anthropic, OpenAI, and Gemini based on accuracy, cost, latency, context needs, security, and fit for the use case
- Integrate AI into existing business systems, APIs, and data sources (CRMs, ERPs, ticketing, document stores, and more)
- Build evaluation, testing, and observability into every deployment so solutions stay accurate and reliable over time
- Automate repetitive processes to eliminate manual work and free people to focus on higher-value tasks
- Train end users, document solutions, and create reusable playbooks and components that can be redeployed across the portfolio
- Measure adoption and impact, and continuously improve deployed solutions based on real-world feedback
- Take on additional AI projects across the portfolio as priorities and opportunities evolve
Skills
- - Hands-on, builder mindset — you prefer shipping working solutions over writing slide decks or managing others
- - 2+ years of software engineering, solutions engineering, forward deployed engineering, or similar hands-on technical experience
- - 1–2+ years building and deploying applications with LLMs in real-world settings
- - Working fluency across major AI platforms (Anthropic Claude, OpenAI, Google Gemini), with a clear understanding of each one's strengths, weaknesses, and trade-offs
- - Experience building agents, agentic workflows, and prompt/context engineering for production use
- - Hands-on experience with enterprise AI platforms such as Microsoft Copilot / Copilot Studio, Microsoft Foundry (formerly Azure AI Foundry), or Amazon Bedrock, and willingness to work across all of them
- - Proficiency in Python and/or TypeScript, SQL, and working with REST APIs
- - Ability to translate ambiguous business problems into concrete technical solutions
- - Comfort working directly with non-technical stakeholders, from frontline staff to company leadership
- - Strong verbal and written communication skills; able to explain AI capabilities and limitations in plain language
- - Self-directed and comfortable juggling multiple projects across different companies in a fast-paced environment
- - Undergraduate degree in Computer Science, Engineering, or a related field preferred, or equivalent practical experience
- - Experience building Claude skills, Claude Code / Agent SDK harnesses, or MCP servers
- - Experience with the OpenAI Agents SDK / Assistants, Google Vertex AI / Gemini APIs, or similar platforms
- - Experience with RAG, embeddings, and vector databases (e.g., Pinecone, pgvector, ChromaDB)
- - Familiarity with agent and orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, Pydantic AI)
- - Experience with LLM evaluation, observability, and guardrails
- - Familiarity with cloud infrastructure (AWS, Azure, or GCP), containers, and Linux environments
- - Experience with workflow automation tools (e.g., n8n, Zapier, Power Automate) and integrating them with AI
- - Prior experience in a forward deployed, consulting, or customer-facing engineering role
Benefits
- Remote position
- Clear path from contractor to full-time employee within a portfolio company as we find the right home for your skills
- Upon conversion to full-time employment: Comprehensive Medical/Rx, Dental, and Vision plans
- Upon conversion to full-time employment: 401(k) program with company match
- Upon conversion to full-time employment: Commuter benefits for parking and transit
Company Overview