Product Manager (AI & LLM)

Spyne; New Jersey; On-site; USD 100,000 - 140,000; Full time

Job summary

A leading automotive technology company in New Jersey seeks an AI Product Manager to drive product strategy for innovative AI-powered applications. The ideal candidate will collaborate with engineers and US dealers, focusing on the roadmap for generative AI solutions. This role demands a customer-centric approach and the ability to integrate AI seamlessly into dealer workflows, ensuring effective adoption and user engagement.

Qualifications

• Strong customer-facing skills with experience in AI products.
• Ability to craft ambitious product roadmaps.
• Experience collaborating with cross-functional teams.

Responsibilities

• Lead product strategy and execution for AI-powered applications.
• Collaborate with data scientists and engineers on LLMs.
• Define and track AI adoption KPIs.
• Work with Sales and Customer Success teams to position AI features.

Skills

AI Platforms & APIs

AI Product Building Blocks

AI Ops & Deployment

Product & GTM Mindset

Soft Skills

Tools

OpenAI

LangChain

Weights & Biases

Job description

Spyne is revolutionizing automotive retail with Generative AI—and we’re moving at lightning speed. We started with a simple but powerful idea: Use AI to help dealers sell cars online faster. Today, we’re building the world’s first AI-powered automotive retail ecosystem, transforming how 350K+ dealers market and sell vehicles across the Globe.

• 5X revenue growth in 15 months—now gunning for 3-4X more this year
• Launched industry-first AI Image & 360° solutions
• Expanding aggressively in the US & Europe
• Next up? A full GenAI Automotive Retail Suite

Role Overview

We’re seeking an AI Product Manager with strong customer facing skills in the New Jersey area to lead product strategy and execution for AI-powered applications—built on LLMs, multimodal AI, and intelligent agents. You’ll sit at the intersection of customers and technology, working closely with US automotive dealers to shape product roadmaps while collaborating with our India engineering & AI teams to bring these to life.

This role is ideal for someone excited by GenAI, LLMs, prompt engineering, and applied AI use cases—who can own both what we build and how we take it to market.

Job Responsibilities

1. Craft a clear, ambitious roadmap for LLM-powered applications and AI agents, keeping user needs, market trends, and technical possibilities in focus.
2. Explore innovative applications of LLMs, such as contextual chatbots, decision-support systems, creative content generators, and automation tools.
3. Collaborate with data scientists and AI engineers to evaluate, fine-tune, and deploy cutting-edge LLMs for real-world use cases.
4. Stay updated on advancements in LLM capabilities, such as multi-turn dialogue, reinforcement learning, in-context learning, and fine-tuning techniques.
5. Define how AI agents integrate with customer workflows, ensuring seamless interaction between humans and AI.
6. Guide the creation of agents capable of handling tasks like scheduling, responding to emails, summarizing documents, extracting insights from data, and automating repetitive processes.
7. Deeply understand user pain points and translate them into impactful AI-driven solutions.
8. Drive adoption by ensuring user-friendly interfaces, explainable AI outputs, and smooth handoffs between human users and AI agents.
9. Cross-functional collaboration: Work with Engineering, Data Science, and Design teams to prototype, test, and deploy LLM-based features at scale.
10. Collaborate with Sales and Customer Success teams to position AI-powered capabilities as a key differentiator.
11. Define and track AI adoption KPIs, and continuously optimize models using metrics like token efficiency, fine-tuned accuracy, and user engagement analytics.

Core Skills & Knowledge

1. AI Platforms & APIs (Awareness of the ecosystem)

• Leading LLMs: OpenAI (GPT), Anthropic (Claude), Google Gemini, Meta LLaMA, Mistral
• Agentic AI Frameworks: LangChain, AutoGPT, CrewAI, Semantic Kernel
• Retrieval & Knowledge: Pinecone, Weaviate, FAISS, vector databases

2. AI Product Building Blocks (Practical PM fluency)

• Fine-tuning & customization of models
• Retrieval-Augmented Generation (RAG)
• Human-in-the-loop workflows & escalation

3. AI Ops & Deployment (Conceptual awareness, not coding)

• Monitoring & evaluation: Weights & Biases, Arize, Humanloop

4. Product & GTM Mindset

• Translate dealer needs → AI features that drive ROI
• Position AI features in GTM with Sales & CS
• Define and track AI adoption KPIs
• Run fast pilots & experiments, measure, iterate

5. Soft Skills

• Customer obsession & empathy
• Clear storytelling: simplify AI for business users
• Bias for action in fast-moving, ambiguous environments