Pay not posted
Forward Deployed Engineer
Posted by Eliza · open on Gem as of
Pay not postedSan Francisco, CA +1Full-time
Forward Deployed Engineer embedding with client teams to design and deliver production-ready AI/ML solutions, from LLM integrations to data pipelines and cloud infrastructure.
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At a glance
Posted base pay
Not posted
Median $190K
Senior FDE postings1,864 postings · middle 50% of posted pay$160K–$220KThe work
Builds what the customer runs
Balance Mostly building
Project stages
- Pre-sales (not covered)
- Proof of concept
- Implementation
- Operations (not covered)
- Coding
- Writes production code
- Builds for
- External customers
- Level
- Senior
- Role
- Individual contributor
What they ask for
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The job description from Eliza
Posted by Eliza on
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.
Job Summary
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.
- Travel opportunities for on-site engagements (if desired).
- Flexibility to work across industries and problem domains.
- A collaborative, mission-driven team passionate about the real-world impact of AI.
About Eliza
AI-native services firm that embeds forward-deployed engineers to enable, build, evaluate, and optimize production AI systems for enterprises.
Seed · 50–100 people
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