The Role:

As CommerceIQ’s first AI Outcome Manager, you will partner closely with our founders and the AI Product Manager to prototype and deploy AI‑driven solutions that solve our customers’ most pressing problems. This is a founding engineering role with high visibility; you will report directly to our co-founder. You will also partner with other members of the executive leadership team who are based at our Mountain View HQ, collaborate with our Bangalore‑based engineering team, and engage daily with enterprise customers. You will help define how we work with our most important customers, shape the company’s first ever forward deployed engineering function, and contribute to our mission of helping brands win in AI‑driven e-commerce.

Location / Travel:

This position is remote with approximately 50% travel expected to client locations.

What You'll Do:

• Build prototypes with customers: Work alongside our AI Product Manager to understand real‑world problems, rapidly scope use cases and create working prototypes. You’ll engage in hands-on discovery and convert insights into functional demos for prospective and existing customers.
• Integrate data and create new AI agents: Ingest data from disparate sources (ERPs, ecommerce platforms, custom APIs) and build agents that solve the specific use cases uncovered during discovery. This includes turning edge‑case business rules into runtime‑editable settings rather than hard‑coded logic.
• Own AI outcomes: Lead customer‑facing demonstrations and proof‑of‑concepts. You’ll instrument and tune models using production feedback loops to ensure prototypes deliver measurable outcomes.
• Rapidly iterate & generalize: Collaborate with engineering teams in Bangalore to transform prototypes into robust features. Your work will be implemented into our core product - patterns that succeed in one deployment (custom adapters, monitoring dashboards) should be packaged as reusable modules.
• Own the full lifecycle: Support engagements from pre‑sales scoping through post‑deployment refinement. You’ll help to negotiate scope, push back on unreasonable asks, and ensure long‑term customer success. Additionally, you’ll act as the technical liaison between customers, product managers, and engineering.
• Cultivate customer relationships: Develop deep empathy for our customers’ business drivers and serve as their advocate. Use clear, engaging communication to convey technical concepts to non‑technical stakeholders, build trust and handle high‑stakes conversations.

What You'll Bring:

• Experienced engineer (5-8 years or more) with a strong foundation in software development (data structures, system design, debugging). Comfortable coding in Python or Java and learning new technologies quickly.
• Full‑stack & data integration skills. Experience connecting to APIs, working with SQL/NoSQL databases, streaming/ETL pipelines and deploying AI/LLM‑based agents.
• Customer‑facing problem solver. You enjoy working directly with external users, conducting discovery, and translating ambiguous requirements into working solutions. You have excellent communication skills and the ability to simplify complex technical topics.
• Rapid prototyper. You are biased towards action and are comfortable delivering minimal‑viable solutions, collecting feedback and iterating quickly.
• Collaborative & global. You’re effective working across time zones with leadership in California and engineering in Bangalore. You embrace CommerceIQ’s leadership principles of ownership, deep diving into details, getting stuff done, thinking from first principles and winning as a team.
• Independent & adaptable. You thrive in ambiguity, can manage your own backlog and priorities, and are motivated by the opportunity to create a new function.
• Bachelor's degree, preferably in Computer Science, Mathematics, or a related field

Nice to Haves:

• Prior experience in a forward‑deployed, solutions engineering or customer implementation role. Candidates coming from companies known for forward‑deployed engineering (e.g., Palantir, Scale AI, Ramp, etc.) are strongly encouraged to apply.
• Familiarity with e-commerce, retail, supply‑chain or ad‑tech data.
• Exposure to large‑language‑model applications (fine‑tuning, prompt engineering, building retrieval‑augmented generation workflows).