AI Product manager

Neureliclabs; Chennai District; On-site; Full time

Job description

At NeuRelic Labs, we’re not just shipping features - we’re designing the future of AI-powered trading and financial systems. As an AI Product Manager, you’ll lead the discovery, planning, and execution of intelligent systems across products.

You’ll sit at the intersection of research, engineering, and user experience - translating complex AI capabilities into impactful product experiences for traders, analysts, and institutions. From LLM-integrated features to algo orchestration tools, this is a hands-on role for builders who think in workflows, not just features.

Responsibilities:

• Define product vision, roadmaps, and success metrics for AI-first features
• Work closely with AI researchers and ML engineers to translate models into usable product components
• Own the end-to-end product lifecycle - from market research and user discovery to release and feedback loops
• Prioritize backlogs, define epics/stories, and ensure product quality in execution
• Collaborate with designers and UX teams to build intuitive, explainable AI interfaces
• Guide experimentation strategy (A/B, metrics instrumentation, etc.) for ML-powered features
• Benchmark competitors, industry trends, and GenAI integrations to keep NeuRelic ahead of the curve

Preferred Qualifications:

• 3-6 years of experience in product management (preferably with AI/ML products)
• Strong understanding of machine learning workflows, model life cycles, and data systems
• Prior experience with fintech, algo trading, or B2B SaaS is highly desirable
• Excellent communication skills - comfortable collaborating with research, design, and business teams
• Familiarity with tools like Figma, JIRA, Notion, MLFlow, or LangChain is a plus
• Bonus: Background in engineering or data science
• Provide expert guidance on developing an AI strategy

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Remote / Hybrid

10 - 12 Lakhs INR

AI Research Specialist

Conducting cutting-edge research in AI, developing new algorithms, and pushing the boundaries of AI capabilities.

Designing and implementing machine learning models and systems, and optimizing algorithms for real-world applications.

Overseeing the development and deployment of AI-powered products and solutions, and working closely with cross-functio