Senior Product Manager, Neo AI

Traba•San Francisco, CA

5d•$180,000 - $210,000•Onsite

About The Position

Traba is building the autonomous future of industrial staffing. We are the AI operating layer for the industrial supply chain. We started in workforce—temp staffing, the biggest operational pain point for the manufacturing and logistics customers we serve—and used it to embed ourselves inside their daily operations and create a far better customer experience through technology. Now those same customers are pulling us beyond staffing into the broader operational workflows that run their facilities. That foundation gave us proprietary data from millions of shifts and deep enterprise relationships. But our edge is more than data: by connecting to the systems running across every facility and activating the workers already on our platform to execute against them, we are building applied AI that drives real productivity gains and transforms how the global supply chain operates at scale. About the Role We’re looking for a Product Manager to build Neo, Traba’s AI agent platform for light industrial businesses. Think Claude for Light Industrial. This is a true 0-to-1 product role operating at the frontier of applied AI. Neo represents our belief that software in industrial environments should do more than surface information or automate isolated workflows. We are building intelligent systems that understand context, reason through ambiguity, make decisions, and execute meaningful work on behalf of users. You’ll operate at the intersection of product, AI, and customer operations while building products in an environment where the underlying model layer is constantly changing. New capabilities emerge, assumptions break, prompts evolve, and product strategy evolves alongside them. You will work directly with engineering, ML teams, founders, and early design partners to define workflows, rapidly ship products, and shape how AI agents transform industrial operations. This role requires exceptional product judgment, comfort operating in ambiguity, deep technical instincts, and the ability to move quickly without large teams or established playbooks.

Requirements

Launched customer-facing AI products where agents took meaningful actions on behalf of users.
Understand systems that execute workflows, orchestrate tools, maintain memory, and perform work autonomously.
Built products from scratch with real customers and understand the realities of finding product-market fit.
Launched products, rebuilt products, changed direction, learned from failure, and iterated rapidly toward customer signal.
Thrive where there is no existing playbook.
Believe great products are built shoulder-to-shoulder with customers.
Experience working in customer-embedded environments or forward deployed product motions is highly valued.
Comfortable building directly with design partners and shaping products through tight customer feedback loops.
Operate alongside ML engineers and highly technical teams as peers.
Can understand evaluations, reason through system tradeoffs, prototype ideas, and participate deeply in technical discussions.
Strong technical instincts and enjoy getting into the details.
Move quickly, operate with urgency, and thrive in environments where assumptions frequently change.
Experience shipping products through model shifts, prompt rewrites, capability cliffs, and rapidly evolving technical environments.
5 to 10+ years of product management experience
Experience building AI-native products, customer-facing agent systems, workflow automation products, developer products, or applied ML systems
Track record of launching products from scratch and shipping products with meaningful customer impact
Strong technical fluency and ability to partner deeply with engineering and ML teams
Strong systems thinking and comfort operating across product, technical, and business constraints
Experience working closely with founders, engineering leadership, and early customers

Nice To Haves

Experience at companies with customer-embedded cultures such as Palantir, Harvey, Sierra, Hebbia, Decagon, or similar environments is highly relevant.
Coding experience
Building prototypes
Experimentation frameworks
Evaluation systems
Direct ML exposure
Experience in AI-native startups and fast-moving product organizations over highly specialized large-company environments.

Responsibilities

Define and own product strategy for Neo and Traba’s broader AI agent ecosystem
Design and build customer-facing AI products that take meaningful action on behalf of users
Partner directly with early design partners and customers to deeply understand workflows and identify opportunities for automation
Rapidly prototype and validate ideas in close collaboration with product engineers and ML teams
Design systems that reason through workflows, orchestrate tools, maintain context, and execute operational work
Define evaluation systems, quality frameworks, and feedback loops that improve reliability and agent performance
Translate ambiguous customer problems into scalable AI systems
Write clear product requirements and work closely with engineering to rapidly ship solutions
Use data, experimentation, and customer insight to identify opportunities and prioritize investments
Launch products iteratively while continuously adapting to model improvements and changing capabilities