Quick Summary
tool/function calling, RAG, prompt architecture, structured outputs, workflow automation. Fluency in at least one major c
PRESHai is hiring Forward Deployed Engineers to build, deploy, and stand up AI systems directly inside client environments across the IT channel.
This is a hands-on delivery role. You will sit at the edge of PRESHai, embedded with MSPs, solution providers, distributors, and manufacturers, turning their business problems into working AI systems that ship in weeks, not quarters. You will be the engineer the client sees, the engineer who writes the code, and the engineer who owns the outcome.
The right person for this role is not a back-office software engineer and not a solutions consultant. This is an operator-engineer who can frame a problem with a senior client stakeholder in the morning, design the solution by lunch, ship a working prototype that afternoon, and harden it into a production system the next day. You move with judgment, not with tickets.
Assignments vary: some FDEs will embed deeply with large enterprise client(s); others will run a portfolio of mid-market engagements. We will determine placement based on fit during the interview process.
You will report directly to the CEO. PRESHai runs a deliberately flat structure: no middle management, high autonomy, and shared context through the systems we build internally on PRESHos. You will pull from the platform, patterns, and tooling built by our Core Engineering team, and you will push reusable patterns back so the next engagement is faster.
Responsibilities
~1 min read- Embed with assigned clients and own the technical execution of PRESHos and AI implementation engagements end to end.
- Translate client workflows, systems of record, and operational pain points into working AI systems. Avoid building things that should not be built.
- Write production code in TypeScript and Python across agents, integrations, workflow orchestration, RAG, and voice interfaces.
- Build and maintain integrations with client CRMs, PSAs, ITSMs, ERPs, communication platforms, databases, and custom internal systems.
- Configure environments, manage credentials safely, and deploy into client or PRESHai-managed infrastructure.
- Drive adoption inside the client. A system that nobody uses is a failed engagement.
- Lead working sessions with client engineering, IT, operations, and business stakeholders.
- Surface blockers, scope creep, and integration risks early and directly.
- Communicate technical decisions and tradeoffs clearly to non-technical stakeholders.
- Train client teams to operate, extend, and trust the systems you ship.
- Build with the architecture, patterns, and tooling defined by Core Engineering; push fixes, missing primitives, and reusable patterns back.
- Maintain observability, error handling, and human-in-the-loop escalation in everything you ship.
Requirements
~1 min read- 3+ years shipping production software, with at least 1 year shipping LLM-powered, automation, or integration systems in production.
- Strong production coding ability in TypeScript and/or Python.
- Practical experience with APIs, databases, OAuth flows, third-party integrations, webhooks, and system-to-system data movement.
- Experience with LLM application patterns: tool/function calling, RAG, prompt architecture, structured outputs, workflow automation.
- Fluency in at least one major cloud ecosystem (Azure/Microsoft 365, AWS, or GCP).
- Experience with PostgreSQL and production observability.
- Comfort sitting in front of senior client stakeholders and owning the outcome, in a fast-moving environment with multiple active workstreams.
- Agentic AI systems, tool-calling systems, MCP servers, or multi-step AI workflows in production.
- AI, automation, or integration implementation in MSP, VAR, distributor, vendor, professional services, legal, or complex B2B environments.
- Microsoft 365 and Azure depth: Graph API, Teams, Entra ID, Bot Service.
- Production voice AI (Twilio, ElevenLabs, OpenAI Realtime API, or similar).
- Workflow orchestration platforms (Inngest, Temporal, or comparable).
- Consulting, agency, or implementation services background.
- Clients see working AI inside their environment within weeks of kickoff.
- Engagements convert from pilot to production to expansion.
- Client engineering and operations teams trust PRESHai because they trust you.
- The patterns you push back to Core Engineering make the next engagement faster.
- Clients describe PRESHai as the team that actually ships.
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- June 11, 2026
- First seen
- June 12, 2026
- Last seen
- June 12, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 53%
- Scored at
- June 12, 2026
Signal breakdown
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