About the Role
We are looking for a Forward Deployed Engineer to bridge the gap between an AI operations platform and the real-world systems used by enterprise customers. You will work directly with clients to understand their processes, technical constraints, and business goals, then design and deliver practical AI-powered solutions within their existing environment.
This is a highly commercial, client-facing engineering role. You will act as both a solution architect and a hands-on engineer, translating customer requirements into working integrations, AI agents, and measurable business outcomes.
What You Will Do
Lead technical discovery with enterprise customers, including C-level and senior business stakeholders.
Understand customer workflows, systems, data sources, and operational challenges.
Scope implementation projects, define success criteria, and translate business requirements into technical solutions.
Design and build integrations between the AI platform and customer systems using Python or JavaScript, SQL, APIs, JSON, and webhooks.
Develop, configure, and deploy LLM-based agents and automation workflows in production environments.
Work with AI evaluation methods, retrieval systems, MCP, and agent frameworks to ensure solutions are reliable and fit for purpose.
Handle real-world deployment constraints, including legacy systems, incomplete documentation, limited APIs, and changing customer requirements.
Communicate technical decisions, risks, and trade-offs clearly to both technical and non-technical stakeholders.
Measure and communicate the business impact of delivered solutions, including efficiency gains, cost savings, and operational improvements.
Act as a trusted technical advisor throughout implementation and post-deployment engagement.
What We Are Looking For
5+ years of experience in software engineering, solutions engineering, technical consulting, or a similar customer-facing technical role.
External, commercial experience working with named enterprise customers of a software product, including scoping work with economic buyers.
Experience working in a venture-backed startup or scale-up, ideally from Seed to Series B, or in a genuine high-growth enterprise environment.
Hands-on experience with Python or JavaScript, SQL, APIs, JSON, and webhooks.
Applied AI experience, including practical work with LLMs, agent frameworks, evaluations, MCP, or retrieval-based systems.
Ability to move comfortably between technical implementation and commercial discussions.
Strong communication skills and the ability to explain complex technical concepts in business terms.
A practical, outcome-driven approach to problem solving.
Full professional fluency in English.
Offer:
A senior, high-impact role shaping how enterprise customers adopt and operationalize AI.
Direct exposure to senior stakeholders and meaningful ownership of customer outcomes.
The opportunity to work on complex, real-world AI deployments rather than isolated proofs of concept.
A collaborative environment that values commercial judgment, technical versatility, and practical execution.