Spyne | Product Manager
10 hours ago
At Spyne, our mission is to revolutionize automotive retailing. Every year, 52 million cars are sold in the US, for a combined worth of $1700 billion, and, valuing the used-car market at $1000 billion. Our new-age, Generative AI-powered solutions are designed to transform the car visuals into premium studio visuals. Dealerships & marketplaces across the US & Europe, are able to better engage their online visitors, driving greater customer showroom visits, and eventually sales.
The Spyne team, located in Gurugram, India, aims to be the leading software provider in the used-car market, addressing all aspects of the dealer journey, from acquiring and appraising cars to listing, marketing, selling, and managing customer relationships. Supported by top investors like Accel Partners and Storm Ventures, as well as experienced founders, we believe in revolutionizing Digital Production for greater efficiency and intelligence. We are among the very few companies in Gen AI space in India, which has truly commercialized the AI, generating hard cash and revenues. We have been consistently featured among the top Gen AI startups coming out of India, and building for the globe.
Read more about us here:
Product - t.ly/t0Ko5
Recent growth - t.ly/bOv3D
Job Description
We are seeking a dynamic Product Manager to lead the development of applications powered by Large Language Models (LLMs) and AI agents This role will focus on harnessing the power of LLMs (e.g., OpenAI’s GPT, Claude, or similar models) to build advanced, context-aware conversational agents and task automation systems. You will work on defining and delivering AI solutions that transform user experiences, streamline processes, and unlock new business opportunities for Automotive dealers and buyers. This role is pivotal in defining Spyne’s product strategy, translating user needs into AI-driven solutions, and working closely with cross-functional teams to deliver innovative products that redefine the user experience.
Job Responsibilities
1. Product Strategy & Vision:
Craft a clear, ambitious roadmap for LLM-powered applications and AI agents, keeping user needs, market trends, and technical possibilities in focus.
Explore innovative applications of LLMs, such as contextual chatbots, decision-support systems, creative content generators, and automation tools.
2. Research & Experimentation with LLMs:
Collaborate with data scientists and AI engineers to evaluate, fine-tune, and deploy cutting-edge LLMs for real-world use cases.
Stay updated on advancements in LLM capabilities, such as multi-turn dialogue, reinforcement learning, in-context learning, and fine-tuning techniques.
3. AI Agent Development:
Define how AI agents integrate with customer workflows, ensuring seamless interaction between humans and AI.
Guide the creation of agents capable of handling tasks like scheduling, responding to emails, summarizing documents, extracting insights from data, and automating repetitive processes.
4. User Experience & Feedback:
Deeply understand user pain points and translate them into impactful AI-driven solutions.
Drive adoption by ensuring user-friendly interfaces, explainable AI outputs, and smooth handoffs between human users and AI agents.
5. Cross-Functional Collaboration:
Work with Engineering, Data Science, and Design teams to prototype, test, and deploy LLM-based features at scale.
Collaborate with Sales and Customer Success teams to position AI-powered capabilities as a key differentiator.
6. Metrics & Performance:
Define measurable KPIs to evaluate AI agent success, including accuracy, response time, user satisfaction, and retention.
Continuously optimize models using metrics like token efficiency, fine-tuned accuracy, or user engagement analytics.
Job Requirements
Basics
3-7 years of product management experience, preferably in AI, SaaS, or data-driven products.
Proven track record of building or scaling AI-powered applications, especially using LLMs like GPT, Claude, or similar frameworks.
Strong familiarity with the functionality of LLMs
Fine-tuning and customization: Adapting pre-trained models to domain-specific tasks.
Prompt engineering: Designing efficient prompts for achieving desired outcomes.
Context management: Optimizing inputs for long, multi-turn conversations or complex tasks.
Model evaluation: Understanding trade-offs between accuracy, latency, and cost.
Other skills
Exceptional communication skills to explain technical AI concepts to non-technical stakeholders.
Analytical mindset with the ability to define and measure success metrics.
Hands-on experience with product development tools (e.g., Figma, Jira) and basic familiarity with LLM APIs (e.g., OpenAI, Anthropic, Hugging Face).
Ability to thrive in a fast-paced, ambiguous environment.
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