Forward Deployed Engineer (AI & Business Automation) | 3–7 Yrs | Bangalore

About company:- 

We are an AI-native franchising and licensing partner helping global brands scale seamlessly across international markets. Our focus is on building intelligent, AI-powered infrastructure that drives smarter decision-making and operational efficiency.

We work on advanced automation across buying, catalog management, inventory optimization, dynamic pricing, and performance marketing — powered by strong data pipelines, marketplace integrations, browser automation, and competitive intelligence systems.

Role: Forward Deployed Engineers

• Location: Bangalore
• Reports to: Head of Product, Engineering & AI
• Experience: 3 - 7 Years
• We require a total of 4 to 5 Forward Deployed Engineers — hiring 3 junior-level and 2 senior-level candidates.

Role Overview: As a Forward Deployed Engineer at Opptra, you will sit at the intersection of business operations and AI systems. Your job is to embed deeply with business teams (Hardlines, Softlines, Supply Chain, Finance, Channel Ops, Brand Ops) to understand real operational problems and rapidly deploy AIand data-driven solutions that automate decisions, reduce manual effort, and improve margins. This role is not about building models in isolation. It is about translating messy workflows, spreadsheets, and tribal knowledge into scalable AI-powered tools, APIs, and automations that the business actually uses. You will work hands-on with marketplaces, OMS/WMS data, web intelligence, and internal systems, partnering closely with non-technical stakeholders and central platform teams.

Key Responsibilities:

● Embed with business teams to deeply understand workflows in catalogue operations, inventory planning, pricing, performance marketing, and supply chain execution.

● Identify high-impact automation and decision-support opportunities and translate them into clear technical problem statements.

● Build and deploy AI-driven solutions such as:

• Decision engines (buying, replenishment, pricing, ad optimization)
• Workflow automations (catalogue QA, exception handling, alerts)
• Internal tools, APIs, and lightweight applications used by ops teams

● Work with data engineers to consume data from marketplaces, OMS/WMS, finance systems, and web-crawled sources via the central data platform.

● Rapidly prototype, test, and iterate solutions in close feedback loops with business users.

● Productionize models and automations with reliability, monitoring, and clear success metrics.

● Help non-technical teams adopt AI tools by simplifying UX, documenting workflows, and embedding AI into daily operating rhythms.

● Act as the “last mile” between AI capabilities and real business outcomes, ensuring solutions drive measurable impact (cost reduction, revenue uplift, time saved).

● Feed learnings back into central AI and data platform roadmaps.

Required Qualifications & Experience :

• 3 - 7 years of experience in software engineering, data engineering, applied AI/ML, or automation-heavy roles.
• Hands-on experience building production-grade systems using Python (preferred), SQL, and modern APIs.
• Practical exposure to AI/ML techniques (optimization, forecasting, classification, LLM-based workflows) with a focus on business outcomes rather than academic novelty.
• Experience working with messy, real-world data from operational systems (e-commerce, marketplaces, supply chain, finance, or ERP/OMS/WMS).
• Comfortable working in fast-moving environments with ambiguous problem statements and evolving requirements.
• Strong ability to work directly with non-technical stakeholders and translate business problems into technical solutions.

Ideal Candidate Profile: You are someone who enjoys being close to the business and gets energy from solving real operational problems. You are equally comfortable debugging a data pipeline, deploying an API, or sitting with a category manager to understand why a spreadsheet exists in the first place. You thrive in environments where problems are underspecified, data is imperfect, and speed matters. You care less about “perfect architecture” and more about building reliable systems that actually get used. You believe AI is valuable only when it changes how people work - and you enjoy being the person who makes that change happen.