Lead Forward Deployed Engineer (AI-Native Software Development )

JetBrains

14d•$204,000 - $306,000•Remote

About The Position

Inside the Professional Services department, we are building a team of Forward Deployed Engineers (FDEs) to enable JetBrains consulting partners to transform their customers' software development lifecycles and to help our customers adopt AI-native development with JetBrains Central, our new platform for agent-driven software development. JetBrains Central connects tools, agents, and infrastructure so enterprises can adopt automated AI workflows with full visibility into results, costs, and processing speed. It provides three core capabilities: Governance and control: Policy enforcement, identity and access management, observability, auditability, and cost attribution for agent-driven work, with some of these capabilities already available via the JetBrains Console. Agent execution infrastructure: Cloud agent runtimes and computation provisioning that allow agents to run reliably across development environments. Agent optimization and context: Shared semantic context across repositories and projects, enabling agents to access relevant knowledge, as well as task routing to the most appropriate models or tools. As a Lead FDE, you will work directly with these customers to deploy JetBrains Central into complex enterprise environments and help early adopters move from experimental AI usage to governed, scalable AI-native development. You will act as a trusted advisor to customer engineering teams and consulting partners, mentor other FDEs, and be responsible for our most complex deployments. Your work in the field will directly influence how our platform evolves and how enterprises adopt agent-driven development. This role combines consulting, architecture, and hands-on engineering. It is often a strong fit for engineers who have previously served as Principal or Staff Engineers, Heads of Engineering, CTOs, or Solutions Architects – and who want to stay close to both customers and complex technical systems.

Requirements

10+ years building or operating production software systems, with at least 3 years in a customer-facing technical role (Solutions Architect, Forward Deployed Engineer, Principal Consultant, or similar).
Proficiency in Java or Python, with the ability to read, debug, and extend customer code in production environments.
Experience building or integrating developer platforms, infrastructure systems, or software solutions.
Demonstrated experience navigating enterprise procurement, security review, and architecture review processes.
Familiarity with modern development workflows (CI/CD, developer environments, internal developer platforms, etc.).
Strong problem-solving skills and the ability to operate in fast-evolving technical environments.
Willingness to travel domestically to customer sites.

Nice To Haves

Hands-on experience with LLM evaluation, prompt engineering at scale, or agent orchestration frameworks (LangGraph, AutoGen, CrewAI, or similar).
Experience operating in environments regulated by SOC 2, FedRAMP, HIPAA, or similar.
Experience with industry-specific solutions (fintech, telco, retail, healthcare, etc.).
Prior experience in solutions engineering, consulting, or forward-deployed engineering roles.
Familiarity with the JetBrains ecosystem or developer productivity tooling.

Responsibilities

Architect and manage deployments of JetBrains Central into enterprise development environments, CI/CD systems, and internal developer platforms.
Mentor and support other FDEs, sharing architectural expertise and scaling the team's deployment practices.
Drive organizations' transition from ad-hoc AI experimentation to governed, AI-native development workflows.
Help organizations establish their own AI governance, including security policies, access management, and data privacy controls.
Enable observability for AI-driven development, helping organizations understand their AI usage and code-generation patterns, as well as AI’s impact on productivity.
Design sustainable AI adoption strategies, including for usage controls and cost visibility across multiple model providers.
Integrate our cloud-based agent execution layer so AI agents run securely and at scale.
Partner closely with JetBrains product teams, shaping the platform based on real-world deployments and customer feedback.
Create delivery frameworks and train JetBrains partners to deliver the desired scope of service.