Principal Forward Deployed Engineer – Applied AI Focus
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Job Description
Principal Forward Deployed Engineer leading complex banking AI projects and integrations. Collaborating with client teams to deliver secure, production-quality AI solutions.
Responsibilities:
- Lead the technical design and delivery of complex banking AI engagements, including off-platform builds and bespoke integrations into client systems
- Partner directly with client engineering, security, and architecture teams — speak their language, respect their constraints, design for their reality
- Architect end-to-end agentic systems: data ingress, model orchestration, evals, observability, security, and the production wrapper around all of it
- Make the call on what to build on Titan's platform vs. what to build bespoke vs. what to push back into our roadmap
- Mentor mid-level FDEs and influence platform direction by codifying what you learn into reusable assets and patterns
- Represent Titan's engineering credibility to banking CTOs, CISOs, and their architects
Requirements:
- A senior engineer with real production scars. You've shipped systems that mattered to real users, at meaningful scale or under meaningful constraint.
- A builder above all. Title less interesting than slope. Many of the best people we know took unconventional paths to get here — that's a feature, not an exception.
- A strong client-facing presence. You can hold your own with a bank CTO, push back on a CISO's threat model with substance, and translate between engineers and executives in real time.
- A systems thinker. You see how a piece fits — and where it doesn't — before you start typing.
- Hypothesis-driven, opinion-strong, ego-light. You commit to a direction, you ship to test it, and you change course when the data says to.
- Banking or regulated-industry experience strongly preferred — financial services, insurance, healthcare, defense, energy, or similar.
- Senior-level full-stack with a strong backend spike — distributed systems, API design, secure integration patterns, infrastructure fluency
- Deep experience building production-grade agents using LangChain, LangGraph, DeepAgents, and model-provider SDKs (Claude SDK, OpenAI Agents SDK)
- Fluency in agent search patterns — agent file search, vector RAG, vectorless RAG — and the tradeoffs between them
- Strong working knowledge of AI security frameworks: observability, data controls, model gateways, prompt and tool-call sandboxing
- Hands-on experience designing and running evals; familiarity with training and fine-tuning loops
- Process orchestration and automation at scale
- Comfort owning architectural decisions across the full stack of a production AI system
Benefits:
- Competitive base salary plus meaningful pre-Series A equity (senior-level grant)
- Remote-first with regular client travel (~30–50%, depending on engagement)
- Unlimited PTO
- 100% of employee medical, dental, and vision premiums covered by Titan
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