Forward Deployed ML Engineer

Role Summary:

As a Forward Deployed AI Engineer, you will work closely with some of our most strategic enterprise customers to deploy LLM-powered agentic solutions tailored to their specific business challenges. You’ll be part of a nimble, high-impact engineering team embedded with customers—building custom agentic workflows, optimizing infrastructure, and shaping product feedback directly into our platform. This is a hands-on engineering role for those who thrive at the edge of product innovation and customer engagement.

What You Will Do

• Build and deploy LLM-powered solutions (agents, RAG pipelines, tools integration) directly with enterprise customers.
• Collaborate with cross-functional teams including Product Managers, Solutions Architects, and Customer Success to understand client requirements and deliver tailored AI solutions.
• Iterate quickly on customer-facing use cases, incorporating feedback loops to improve model and system performance.
• Support customers in implementation, fine-tuning, and integration of LLMs in production environments.
• Share insights from deployments with core engineering and product teams to influence roadmap and feature prioritization.
• Occasionally travel to customer sites or participate in virtual workshops and implementation sessions.

Key Responsibilities:

Customer-Embedded Engineering

• Work closely with enterprise customers to understand their workflows and define solution architectures involving AI agents, LLMs, and retrieval systems.
• Translate real-world customer problems into deployable AI workflows using planning, memory, retrieval, and tool integration.

Hands-on AI Systems Development

• Implement and optimize agentic AI systems using LLMs and tool orchestration frameworks (e.g., LangChain, RAG pipelines).
• Conduct prompt engineering, performance evaluation, and fine-tuning to improve solution effectiveness and reliability.
• Collaborate with product and platform teams to identify reusable patterns and influence roadmap based on deployment learnings.

Customer Feedback & Support

• Serve as a technical point of contact during deployments and early adoption phases.
• Capture feedback from real-world usage and help prioritize improvements and fixes.

Requirements:

Must-Have

• 3+ years of experience in ML, NLP, or software engineering, with recent exposure to LLMs and agentic workflows.
• Strong programming skills in Python and relevant libraries (Transformers, LangChain, FastAPI, etc.).
• Experience with cloud infrastructure and deploying ML models in real-world settings.
• Ability to work directly with customers and translate business problems into AI solutions.
• Familiarity with vector databases, retrieval systems, and prompt engineering best practices.

Nice-to-Have

• Prior experience in a forward-deployed, customer-facing, or consulting engineering role.
• Exposure to compliance and enterprise deployment constraints (e.g., PII, data governance).
• Background in MLOps, data pipelines, or orchestration tools (Ray, Airflow, etc.).