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About Us
At Turgon AI, we’re reimagining how enterprise IT services are delivered by combining AI agents and forward-deployed engineers to build, integrate, and automate the enterprise data stack.
Our vision is to create the AI-Native Accenture — where autonomous agents understand your ERP, CRM, and data systems and can deliver full-fledged data pipelines, insights, and system integrations. This is a $1.5T transformation opportunity, and we’re building the core team to make it real.
If you’re a product leader who can code, think systemically, and thrive at the intersection of engineering, AI, and enterprise data — we’d love to talk.
About the Role
We’re looking for a Technical Product Manager to lead the productization of our AI Agent Platform that delivers automated data pipelines from ERP and SaaS systems into Snowflake’s medallion architecture (Bronze → Silver → Gold).
This is a hybrid role — part product manager, part project lead, and part technical operator. You’ll own product definition and roadmap, manage multi-agent orchestration use-cases, and lead forward-deployed engineers executing real client implementations.
You’ll work closely with the founders to define our agentic workflow engine, customer experience, and deployment playbooks — and translate deep technical complexity into elegant, usable, enterprise-grade products.
Responsibilities
- Define and own the roadmap for Turgon’s multi-agent platform and its integration with ERP, CRM, and data-warehouse ecosystems.
- Translate customer problems into detailed product specs — APIs, workflows, agent behaviors, UI/UX flows, and orchestration logic.
- Act as technical bridge between customers, engineers, and researchers — ensuring clarity, delivery, and continuous improvement.
- Lead and coordinate forward-deployed engineering pods delivering client solutions; ensure timelines, scope, and quality.
- Manage backlog, sprints, and cross-functional execution across AI, backend, and data teams.
- Define success metrics (latency, accuracy, cost per job, automation coverage, etc.) and drive iterative improvements.
- Partner with leadership on go-to-market strategy, pricing, and product packaging for enterprise clients.
- Stay on top of emerging developments in LLMs, LangGraph, dbt, Dagster, and Snowflake Tasks/Streams ecosystems to guide roadmap evolution.
Requirements
- 4–8 years of experience in technical product management, data engineering, or AI-powered product development.
- Strong coding foundation (Python, SQL, or JS) — comfortable reading and writing production-level code.
- Experience in data pipeline, ETL, or AI orchestration environments (Snowflake, dbt, Airflow, Dagster, etc.).
- Demonstrated experience working with enterprise clients and managing end-to-end technical delivery.
- Exceptional ability to structure ambiguity into clarity — requirements, specs, timelines, and measurable impact.
- Excellent written and verbal communication; ability to convey complex technical concepts to engineers and executives alike.
- Proven experience leading cross-functional teams under startup-speed conditions.
Nice to Have
- Experience with LangChain, LangGraph, or OpenAI Assistants API.
- Prior work in enterprise automation, ERP integration, or agentic systems.
- Background in ML, data engineering, or software architecture.
- Prior startup or early-stage experience, especially in technical founder or PM roles.
What We Offer
- Competitive compensation with meaningful equity (ESOPs).
- Hybrid, global culture with bases in San Francisco and New Delhi.
- Leadership role shaping one of the most advanced AI-native integration platforms in the world.
- Access to top AI researchers, engineers, and advisors across the U.S. and India.
- A fast, transparent, and execution-driven environment where product decisions happen daily.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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