Forward Deployed Engineer
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.