Senior Forward Deployed Engineer

About Enlighten

At Enlighten, we believe AI should expand what people can take on. We build teams of AI agents alongside Fortune 500 companies so they can put their best thinking to work across the business. We want the people closest to the work to be able to ask hard questions and get answers they can trust. Our mission is to give every team the intelligence it needs to make decisions that shape the business.

About the role

You'll work directly with customers to turn hard business problems into software their teams can use in production. You'll lead the technical work from discovery through rollout, make the calls that shape the deployment, and help other engineers deliver it.

What you'll do

• Lead technical discovery with customers. Turn business needs, data constraints, and security requirements into a plan the team can deliver.
• Lead integrations that connect governed enterprise data and agent workflows to the BI tools and operating routines customer teams already use.
• Run multiple AI agents in parallel every day to investigate customer systems, prototype integrations, and build custom diagnostics and test tools. Verify the results against the customer's acceptance criteria.
• Own production readiness. Set up access controls, automated checks, and monitoring, and give customers and support teams what they need to operate the deployment.
• Trace failures across the application, data, and infrastructure. Explain tradeoffs and raise risks early enough for the team to act.
• Coach engineers through delivery and work with the product team to turn recurring customer needs into reusable improvements.
• Work with customer analysts to turn their business rules and evals into production acceptance checks. Own how those checks run when an analysis is repeated, how failures are monitored, and when outputs go to human review.

What you bring

• Senior ownership of software delivered into real customer environments, including decisions about architecture, rollout, and ongoing reliability.
• Strong Python or TypeScript skills, practical SQL, and the ability to work across APIs, databases, and a modern application frontend.
• Experience with cloud infrastructure and enterprise authentication, permissions, and integration constraints.
• Hands-on experience coordinating multiple AI agents and building custom apps or developer tools, with a clear method for checking generated work.
• Sound judgment about when to experiment, when to ask a focused question, and when a change needs customer or engineering review.
• The ability to work independently through an unfamiliar system and explain technical decisions to both engineers and business stakeholders.
• A habit of documenting decisions, testing assumptions, and staying accountable through the final handoff.
• Experience deploying analytics or AI products with enterprise data warehouses such as Snowflake, BigQuery, or Databricks.
• Experience with FastAPI, React, Google Cloud, or AWS.
• Experience mentoring engineers on customer delivery or building reusable deployment patterns.
• You work independently. You can take an unclear goal, decide what to do first, find what you need, and carry the work through to a result. You bring people in early when a decision, risk, or dependency needs their input.

How we work

AI agents are core to how we get work done. You'll spend a substantial part of your day running multiple agents in parallel, building tools and workflows with them, and checking what they produce. You own the result. Verify the facts, calculations, code, and claims before they go into a decision, a customer conversation, or a release.

When working with clients, take initiative within the agreed goals, scope, access permissions, and review process. Bring options and recommendations, and involve the right people before changing a customer commitment or production workflow.

What success looks like

• Customers can use the deployed workflow to complete the agreed business task, and the result meets the acceptance criteria.
• Your implementations are tested, documented, supportable, and clear about their limits.
• Reusable tools and patterns reduce repeated delivery work across customers.
• AI agents increase the team's capacity while you retain ownership of technical quality and customer commitments.