Turgon AI

AI-native system integrator for data modernization

Product Manager - AI Agent Platform, Technical Product Manager

Technical Product ManagementConfirmed live in the last 24 hours

Full-timeDelhi, IndiaIn-person

About the Job

Requirements

Four to eight years of experience in technical product management, data engineering, or artificial-intelligence-powered product development.
A strong coding foundation in Python, SQL, or JavaScript, with the ability to read and write production-level code.
Experience in data pipeline, extract-transform-load, or artificial intelligence orchestration environments such as Snowflake, dbt, Airflow, or Dagster.
Demonstrated experience working with enterprise clients and managing end-to-end technical delivery.
The ability to structure ambiguity into clear requirements, specifications, timelines, and measurable impact.
Excellent written and verbal communication, with the ability to convey complex technical concepts to engineers and executives.
Proven experience leading cross-functional teams in startup-speed conditions.

Responsibilities

Define and own the roadmap for the multi-agent platform and its integration with enterprise resource planning, customer relationship management, and data-warehouse ecosystems.
Translate customer problems into detailed product specifications covering application programming interfaces, workflows, agent behaviors, user-interface and user-experience flows, and orchestration logic.
Act as the technical bridge between customers, engineers, and researchers to ensure clarity, delivery, and continuous improvement.
Lead and coordinate forward-deployed engineering pods delivering client solutions, ensuring timelines, scope, and quality.
Manage the backlog, sprints, and cross-functional execution across artificial intelligence, backend, and data teams.
Define success metrics, including latency, accuracy, cost per job, and automation coverage, and drive iterative improvements.
Partner with leadership on go-to-market strategy, pricing, and product packaging for enterprise clients.
Monitor developments in large language models, LangGraph, dbt, Dagster, and Snowflake Tasks and Streams to guide roadmap evolution.

Desired Qualifications

Experience with LangChain, LangGraph, or the OpenAI Assistants application programming interface.
Prior work in enterprise automation, enterprise resource planning integration, or agentic systems.
A background in machine learning, data engineering, or software architecture.
Prior startup or early-stage experience, especially in technical founder or product management roles.

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.

About the Company

Turgon AI

AI-native system integrator for data modernization

Turgon AI is an AI-native system integrator that helps large enterprises modernize their IT and data infrastructure. It combines proprietary AI agents with human experts to convert legacy, siloed systems into AI-ready data foundations. Its platform covers data migration, system consolidation and integration, data governance, and analytics enablement, working with enterprise systems such as Salesforce, Snowflake, Databricks, SAP, and Oracle. The company serves customers in logistics, supply chain, hospitality, finance, and retail, and highlights case studies like McCarthy Tire Service and Penguin Solutions. Turgon differentiates itself by integrating AI-powered agents with human expertise to perform data modernization end-to-end, rather than relying on traditional, purely human-driven system integration. Its goal is to help enterprises unlock value from their data by creating unified, governable data foundations that enable scalable analytics and AI initiatives.

Company size: 11-50
Company stage: Seed
Total funding: $6.5M
Headquarters: San Francisco, CA
Founded: 2024

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