Forward Deployed Solution Engineer – Applied AI

This is a fully remote position, open to applicants in New York.

📋 Description

• Collaborate closely with clients to identify challenges and define impactful AI use cases.

• Create and develop comprehensive GenAI/ML systems, encompassing RAG pipelines, agentic workflows, evaluations, and safeguards.

• Deploy AI systems into production environments.

• Rapidly prototype, iterate with actual users, and refine pilot projects into dependable, monitored services.

• Manage the technical relationship between business stakeholders and the engineering team.

• Facilitate communication between business stakeholders and engineers.

• Develop libraries, prompts, and scaffolds that support various deployments and projects.

• Influence internal tooling and contribute to the platform roadmap and foundational elements.

• Lead implementations from concept to execution.

• Deliver solution-ready builds in agile sprints in collaboration with customers.

• Enhance the depth of ML knowledge and engineering quality throughout the team.

⛳️ Requirements

• Over 8 years of experience in software engineering.

• More than 2 years of experience in customer-facing or embedded roles.

• Experience in developing machine learning/GenAI systems utilizing LLMs, embeddings, vector databases, and RAG architectures.

• Demonstrated ability to design and implement AI-native software in production settings.

• Proficiency in backend technologies such as Python, Node.js, and Java.

• Frontend expertise with React and Angular.

• Familiarity with REST/GraphQL APIs.

• Knowledge of LangChain, Semantic Kernel, prompt chaining, vector search, and context management.

• Expertise in troubleshooting distributed systems, optimizing for latency, and setting up monitoring systems.

• Capability to contribute to shared SDKs and tools.

• A product-oriented mindset focused on user value, MVP iteration, and long-term scalability.

• Experience with deployments in AWS, Azure, or GCP, including CI/CD, containers, and infrastructure-as-code.

• Willingness to travel up to 30% for onsite embedding and delivery.

• Background in integrating AI into work processes, decision-making, or problem-solving.

• Preferred: experience in integrating AI into SaaS platforms such as ServiceNow or Salesforce.

• Preferred: proven record of production deployments in secure, regulated enterprise environments.

• Preferred: contributions to developer-experience tooling, frameworks, or reusable AI scaffolds.

🏝️ Benefits

• Equity (when applicable).

• Variable/incentive compensation.

• Health plans.

• Flexible spending accounts.

• 401(k) Plan with company match.

• Employee Stock Purchase Plan (ESPP).

• Matching donations.

• Flexible time-away policy.

• Family leave programs.