Forward Deployed Engineer

Eliza; United States; On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Competitive compensation

Equity options

Flexible work across industries

Job summary

Eliza is seeking a Forward Deployed Engineer (FDE) to work directly with clients, translating business needs into scalable AI solutions. The role involves leading the technical design and implementation of AI systems, collaborating across teams, and advising on best practices for AI/ML. Candidates should have 2+ years in software engineering, strong skills in Python, and experience with cloud platforms like AWS or GCP. Eliza offers competitive compensation, equity options, and a collaborative work environment with a focus on real-world AI impact.

Qualifications

• 2+ years of software engineering experience, ideally in full-stack or backend roles.
• Hands-on experience delivering real-world ML/AI projects.
• Strong programming skills in Python; familiarity with JavaScript/TypeScript, or Go is a plus.

Responsibilities

• Partner with clients to understand business needs and constraints.
• Lead technical design and implementation of AI systems.
• Collaborate with internal teams to enhance service delivery.

Skills

Software engineering

Machine Learning

Python

Client communication

Cloud platforms

Tools

TensorFlow

PyTorch

AWS

GCP

Azure

Job description

About Us

We are a technology services company 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

We are seeking a Forward Deployed Engineer (FDE) to work closely with our clients, translating complex business needs into scalable, production‑ready AI solutions. As an FDE, you will serve as the technical face of our company on the ground—embedding with client teams, shaping solution architectures, and ensuring successful delivery. This role is perfect for engineers who love solving real‑world problems, working directly with customers, and navigating the intersection of consulting and engineering.

Key Responsibilities

1. Client‑Facing Solution Delivery

• Partner directly with client stakeholders to understand requirements, constraints, and business objectives.

• Lead the technical design and hands‑on implementation of custom AI systems—including model integration, data pipelines, APIs, and deployment infrastructure.

• Rapidly prototype and iterate with clients in live environments.

2. Full‑Stack AI Engineering

• Build and deploy ML/AI solutions using technologies like Python, TensorFlow/PyTorch, LangChain, and cloud‑native tools.

• Integrate LLMs and other generative models into client products and workflows.

• Support model fine‑tuning, prompt engineering, and evaluation pipelines where applicable.

3. Cross‑Functional Collaboration

• Work with internal teams (product, design, research) to shape reusable components and frameworks based on deployment experiences.

• Contribute client feedback and frontline insights to improve service delivery and product strategy.

4. Technical Advisory & Enablement

• Advise client technical teams on best practices for AI/ML development and deployment.

• Deliver hands‑on workshops, documentation, and training to enable long‑term client success.

• Guide clients through infrastructure and architecture decisions (e.g., cloud, security, scalability).

Qualifications

Required

• 2+ years of software engineering experience, ideally in full‑stack or backend‑focused roles.

• Hands‑on experience delivering real‑world ML/AI projects, either independently or in collaboration with data science teams.

• Strong programming skills (Python required; familiarity with JavaScript/TypeScript, Go, or similar a plus).

• Comfort with modern cloud platforms (AWS, GCP, or Azure) and CI/CD workflows.

• Excellent communication and client interaction skills.

Preferred

• Experience with LLMs (e.g., OpenAI, Anthropic, Cohere), vector search, or prompt engineering.

• Prior consulting, professional services, or customer‑facing technical roles.

• Familiarity with MLOps practices and tools (e.g., MLflow, Weights & Biases, SageMaker).

• Knowledge of common enterprise security, data privacy, and compliance constraints.

What We Offer

• Competitive compensation (salary + deployment bonuses or client uplift incentives).

• Equity options in a growing AI services company.

• Flexibility to work across industries and problem domains.

• A collaborative, mission‑driven team passionate about the real‑world impact of AI.