Forward Deployed Engineer

About Us

Job Summary

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.