Eliza
via Ashby
Forward Deployed Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 174d ago
The date the source published, not the day we noticed it (2026-03-24). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $160k–225k/yr
Middle 50% of 2159 listings that do state pay — Engineering · all levels · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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ashby employer's own board first seen 11d ago · last seen just now
The listing
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.