Forward Deployed AI Engineer

Forward Deployed AI Engineer

Employment Type: Full-Time
Work Arrangement: 100% Remote
Experience Level: Senior

About the Role

Our client is seeking a Forward Deployed AI Engineer to work directly with customers and deliver production-ready AI solutions.

This is a hands-on engineering and consulting role. You will understand customer business processes, identify practical AI use cases, build working solutions, and lead implementations from prototype through production.

The ideal candidate combines strong AI and software engineering skills with excellent communication and the ability to work effectively in remote, client-facing environments.

Responsibilities

Lead remote technical discovery sessions with customers.

Understand customer workflows, data, systems, and technical constraints.

Convert business requirements into AI architectures and implementation plans.

Build applications using LLMs, RAG, AI agents, machine learning, and workflow automation.

Develop backend services, APIs, data pipelines, and system integrations.

Connect AI solutions with databases, document repositories, SaaS platforms, and internal APIs.

Implement structured outputs, tool calling, human approval workflows, guardrails, and fallback logic.

Evaluate model accuracy, retrieval quality, latency, reliability, security, and cost.

Deploy AI services into customer cloud or enterprise environments.

Troubleshoot technical issues during implementation and production rollout.

Communicate progress, risks, and technical decisions to customer stakeholders.

Document system architecture, deployment procedures, and implementation decisions.

Share reusable solutions and customer feedback with internal engineering teams.

Required Qualifications

Five or more years of professional software engineering experience.

Strong production experience with Python.

Experience building and deploying LLM, machine learning, NLP, or AI-powered applications.

Experience with RAG, embeddings, vector databases, tool calling, or AI agent workflows.

Experience building backend services using FastAPI, Django, Flask, or similar frameworks.

Experience integrating enterprise APIs, databases, and third-party platforms.

Experience with AWS, Azure, or Google Cloud.

Experience with Docker, CI/CD, automated testing, monitoring, and production support.

Strong problem-solving and technical ownership skills.

Excellent written and spoken English.

Ability to communicate technical concepts clearly to technical and non-technical customers.

Ability to work independently and collaborate effectively with distributed teams.

Preferred Qualifications

Experience in technical consulting, professional services, solutions engineering, or customer-facing software delivery.

Experience with OpenAI, Anthropic, Google Gemini, AWS Bedrock, or open-source language models.

Experience with PostgreSQL, pgvector, Pinecone, Qdrant, Weaviate, OpenSearch, or similar technologies.

Experience deploying AI systems in secure enterprise environments.

Knowledge of AI evaluation, observability, privacy, and responsible AI practices.

Experience leading technical workshops or mentoring engineers.

What Success Looks Like

Customer requirements are converted into practical and maintainable AI solutions.

Prototypes progress into stable production deployments.

AI systems are reliable, secure, measurable, and grounded in customer data.

Technical risks and limitations are communicated clearly.

Delivered solutions provide measurable value to customers.

Customer engineering teams can understand, operate, and maintain the implemented systems.

How to Apply

Please submit your resume and GitHub profile or technical portfolio, if available.