AI Engineer

As a Forward Deployed Engineer (FDE) on Rocketlane's AI Implementation team, you will own the technical success of our strategic customers as they adopt Nitro AI agents. You'll embed with customer teams - running discovery, designing agent workflows, configuring integrations, engineering prompts, and shipping production-grade apps and agents that drive measurable outcomes.

This is a hands-on, high-ownership role that sits at the intersection of engineering, product, and customer success. You'll understand customer workflows, orchestrate agents, write code, debug live issues, and translate what you learn in the field into product improvements that shape the future of Nitro. If "professional services consultant" feels too removed from the keyboard and "pure product engineer" feels too removed from the customer, this role is built for you. You'll be a founding member of our AI-first Professional Services org - someone who thrives in ambiguity, loves solving puzzles, and is energised by seeing their work live in production within weeks, not quarters.

The candidate will have responsibilities across the following functions:

Customer-Embedded Agent Deployment:

• Own end-to-end deployment of Nitro AI agents for enterprise customers - from discovery and solution design to configuration, go-live, and ongoing optimisation. Lead technical discovery sessions with customer stakeholders (Services leaders, IT, Operations, Revenue teams) to map business workflows to Nitro agent capabilities.
• Design agent architectures that solve real delivery problems: migration agents, workforce agents, documentation agents and custom workflows tailored to each customer's environment.
• Build and deploy custom integrations between Nitro and customer systems (CRM, HRMS, ERP, Finance tools, data warehouses, internal APIs).

Hands-On Engineering:

• Write production-grade code/ scripts to extend, customise, or integrate Nitro agents into customer workflows.
• Engineer prompts, design evaluation frameworks, and tune agent behaviour for customer-specific data, terminology, and edge cases.
• Build data pipelines and connectors to feed agents with the right context - SOWs, project history, customer communications, and structured delivery data.
• Debug live agent behaviour in customer environments, perform root-cause analysis on complex system interactions, and ship fixes fast.

Trusted Technical Advisor:

• Serve as the technical point of contact for strategic accounts throughout their Nitro implementation journey.
• Guide customers toward best-practice implementations - and push back when needed.
• Your job is to advise, not just execute requirements.
• Translate customer pain into clear problem statements, then into shipped solutions.
• Our model is simple: spend time understanding customer workflows, then build agents.

Product Feedback Loop:

• Be the voice of the customer inside Rocketlane.
• Surface patterns, edge cases, and feature gaps to our Product and Engineering teams.
• Prototype and validate new agent capabilities in the field before they become full product investments.
• Contribute to internal playbooks, reusable agent templates, and scaled enablement content so every FDE engagement makes the next one faster.

Pre-Sales and POC Support:

• Partner with Sales and Solutions teams on high-stakes enterprise deals - building rapid POCs, running technical validations, and proving the business case for Nitro.
• Represent Rocketlane's technical depth in customer executive conversations, demos, and architecture reviews.

The core requirements for the job include the following:

Engineering and Technical Depth:

• 3-5 years of hands-on software engineering/product management experience, with the ability to write production-grade code in at least one of Python, TypeScript/JavaScript, or similar.
• Strong command of REST APIs, webhooks, OAuth/auth flows, and enterprise integration patterns - you can read API docs, test endpoints, and ship integrations without hand-holding.
• Good understanding of data modelling and ETL - comfortable working with messy enterprise data and shaping it for production use.
• Comfortable with modern cloud, DevOps, and integration tooling (Postman, AWS/GCP, Docker, iPaaS platforms like Workato/Boomi/Make).

AI and Agent Engineering:

• Hands-on experience building with LLMs and AI agent frameworks - prompt engineering, agent orchestration and evaluation/guardrails.
• Comfortable using AI-assisted development tools (Cursor, Claude Code, Replit, Lovable, or similar) to move faster and build utilities that make deployments scalable.
• Strong intuition for when to use an agent vs. deterministic automation, and how to design human-in-the-loop workflows that customers trust.

Requirements:

• 1+ years in a customer-facing technical role - Solutions Engineering, Forward Deployed Engineering, Technical Consulting, Implementation, or similar at a B2B SaaS or AI company.
• Proven ability to drive enterprise deployments end-to-end with minimal supervision, including discovery, solutioning, and leading technical conversations.
• Excellent written and verbal communication - you can sit in a room with a VP of Services and earn their trust, then turn around and write clean technical documentation.
• Ability to simplify complex AI concepts for non-technical stakeholders.

Problem-Solving and Ownership:

• Bias toward action and ownership. You see a problem, you fix it. You don't wait for a ticket.
• Strong first-principles thinking - you can decompose a messy customer problem into a solvable, shippable plan.
• Thrives in ambiguity. Comfortable operating without a playbook, because you're often the one writing it.

Good-to-Have Skills:

• Experience with Professional Services Automation (PSA) tools - Rocketlane, Asana, Wrike, ClickUp, Salesforce PSA, Kantata, etc.
• Background in Professional Services, Customer Success Engineering, or technical implementation at enterprise SaaS companies.
• Prior exposure to building or deploying agentic AI systems in production at an AI-native or AI-forward company.

Skills

API, AWS, Docker, ETL, JavaScript, LLM, OAuth, Prompt Engineering, Python, REST, TypeScript, Webhooks