- Location
- Bengaluru, Karnataka, India
- Job type
- Full-time
Required skills
- AWS
- API
- Azure
- compliance
- data science
- end-to-end
- GCP
- multi-tenant
- PRDs
- product design
About the role
Promaynov Advisory Services Pvt. Ltd
Website:
promaynov.com
Job details:
How will you contribute?
- Lead discovery and translating business goals to precise AI problem statements.
- Design AI user journeys and interaction patterns
- Collaborate with Design to prototype AI-native interaction models: conversational interfaces, co-pilots, autonomous agents, and ambient AI experiences.
- Define and own the AI product principles and Drive model selection strategy across products.
- Design and own the core AI platform stack: LLM gateway, prompt management service, context/memory layer, retrieval infrastructure (RAG), and evaluation harness.
- Establish Ai Products in compliance with platform reliability and Responsible Ai practices
- Infuse Ai Platform Observability, Evaluation and Continuous Improvement practices.
- Own Ai Products / Platform Deployment, AI Product marketplace and Commercial monetization.
- AI Product Design & Strategy - Own the end-to-end AI product strategy: set the vision, define north-star metrics, and build a prioritised roadmap across multiple AI product surfaces.
Qualifications
- 10+ years of experience in Data Science & AI Engineering and 3+ years in AI/ ML Product and Platform roles.
- Bachelor's or master’s in engineering, Data Science or Product engineering
- Demonstrable track record designing and shipping AI platforms or AI-first products at scale.
- Strong platform engineering fundamentals: API design, distributed systems, reliability, observability.
- Experience building multi-tenant, API-first services on AWS, GCP, or Azure.
- Familiarity with Large Language Model (LLM) risk landscapes, including hallucination, prompt injection, and model misuse.
- Deep expertise in LLM systems: RAG, fine-tuning, RLHF, prompt engineering, context management.
- Ability to write and own PRDs, strategy documents, and architecture decision records (ADRs).
- Strong product intuition — can interview users, define metrics, and make prioritisation calls.
- Strong communication, stakeholder management, and team leadership skill
Nice To Have
- Experience building internal AI developer platforms or AI-as-a-Service products.
- Familiarity with agentic frameworks: LangGraph, AutoGen, CrewAI.
- Exposure to multimodal AI — vision, audio, document intelligence
- Background in financial services, healthcare, or regulated industries
- Prior experience at a platform company or AI-first startup (Series B+).
- Strategic thinking to define long term AI-governance vision and bring in regulatory acumen.
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