Senior Forward Deployed Engineer

Eliza; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Eliza is seeking a Senior Forward Deployed Engineer to tackle the toughest client problems, owning architecture and delivery end-to-end. This senior IC role emphasizes deep technical execution with direct client exposure while maintaining hands-on engineering work.

You will review critical work before client delivery, mentor teammates, and contribute to technical standards. The role targets engineers who crave hard problems and robust client collaboration without a management track.

Qualifications

• 5+ years of software engineering experience including backend or full-stack depth.
• Track record of independently owning complex, ambiguous technical work from definition through production.
• Strong programming skills in Python; fluency in at least one additional language (JavaScript/TypeScript, Go, or similar).
• Demonstrated experience delivering real-world ML/AI systems in production.
• Deep comfort with modern cloud platforms (AWS, GCP, or Azure), infrastructure-as-code, and CI/CD workflows.
• Excellent client communication: able to hold a room, explain tradeoffs, and deliver bad news early.
• Sound architectural judgment and the instinct to elevate at the right moment.

Responsibilities

• Own end-to-end delivery quality for a major engagement, workstream, or solution area and translate needs into practical plans and milestones.
• Lead solution architecture and technical decisions, balancing speed, quality, scope, maintainability and cost.
• Design and ship AI/ML solutions using Python, ML frameworks, LLM tooling, and cloud-native infrastructure; manage fine-tuning and retrieval pipelines where needed.
• Act as the senior technical voice on the engagement, communicating clearly to technical and non-technical audiences and managing expectations.
• Spot risks early and escalate with context, options, and a recommendation to keep delivery on track.
• Mentor less experienced engineers through reviews, pairing, and contributing to interviews and technical standards.

Skills

Python

JavaScript/TypeScript

Go

Job description

Senior Forward Deployed Engineer

About Us

Eliza is a technology services company and Advanced-tier OpenAI partner that's dedicated to helping organizations build and deploy cutting-edge AI solutions. From generative AI and custom LLM integrations to predictive analytics and intelligent automation, we work across industries to bring real-world AI applications to life. Our projects combine deep technical expertise with hands-on client collaboration to solve high-impact problems.

Role Overview

The Senior Forward Deployed Engineer (Senior FDE) executes the core technical work on our hardest client problems. This is a senior individual contributor role with real depth: you take ambiguous, high-stakes work from problem definition through shipped outcome, own the architecture and the tradeoffs, and set the technical standard clients experience.

Senior FDEs go deep on a major engagement or workstream rather than broad across a portfolio. You are the person we send when the problem is genuinely difficult, the requirements are unclear, and the client needs someone who can hold the technical line while still shipping. You will review critical work before it reaches clients and lift the engineers around you through pairing, review, and example.

This role is for engineers who want the hardest technical problems and direct client exposure without trading hands-on work for a management track.

Key Responsibilities

1. Own end-to-end delivery quality for a major engagement, workstream, or solution area. Translate ambiguous client needs into practical execution plans, technical milestones, and shipped outcomes. Maintain a clear view of status, risks, blockers, and dependencies within your scope. Raise quality concerns early and correct course before client confidence is affected.




2. Lead solution architecture and technical decision-making for your workstream. Make pragmatic tradeoffs between speed, quality, scope, maintainability, cost, latency, and client value-and explain your reasoning. Review critical technical work before it is shared with clients or treated as production-ready. Recognize when a problem needs deeper expertise or a second set of eyes. Turn hard-won solutions into reusable patterns that raise the floor for future engagements.




3. Design and ship AI/ML solutions using Python, modern ML frameworks, LLM orchestration tooling, and cloud-native infrastructure. Integrate LLMs and other generative models into client products and workflows at production quality. Own fine-tuning, prompt engineering, retrieval, and evaluation pipelines where the problem calls for them. Make sound decisions about security, data privacy, and compliance constraints in enterprise environments.




4. Act as the senior technical voice on your engagement, credible with both engineers and executives. Communicate direction, tradeoffs, risks, and progress clearly to technical and non-technical audiences. Manage expectations with discipline when scope, timeline, data, or technical constraints change. Keep account and commercial partners informed so client strategy reflects delivery reality.




5. Spot technical, delivery, scope, timeline, and client-alignment risks early. Resolve what you can directly; elevate what you cannot, with clear context, options, and a recommendation. Intervene decisively within your scope when quality, pace, or client confidence is at risk.




6. Mentor less experienced FDEs through technical review, pairing, and practical feedback. Help teammates make better architecture, implementation, and communication decisions. Model what excellent forward-deployed execution looks like in client-facing work. Contribute to interview loops, onboarding, and technical standards.

Qualifications

Required

• 5+ years of software engineering experience, including significant backend or full-stack depth.


• Track record of independently owning complex, ambiguous technical work from definition through production.


• Strong programming skills in Python; fluency in at least one additional language (JavaScript/TypeScript, Go, or similar).


• Demonstrated experience delivering real-world ML/AI systems in production, not just prototypes.


• Deep comfort with modern cloud platforms (AWS, GCP, or Azure), infrastructure-as-code, and CI/CD workflows.


• Excellent client communication: you can hold a room, explain a tradeoff, and deliver bad news early.


• Sound architectural judgment and the instinct to elevate at the right moment rather than the last moment.

Preferred

• Substantial production experience with LLMs (e.g., Anthropic, OpenAI, Cohere), vector search, retrieval-augmented generation, or agentic systems.


• Prior consulting, professional services, solutions architecture, or forward-deployed engineering experience.


• Familiarity with MLOps