Forward Deployed Engineer

About Opptra:

Opptra (www.opptra.com) is revolutionizing global expansion for consumer brands with a focus on ecommerce and digital capabilities. We're building a portfolio of category-specialized franchising businesses, powered by our centralized technology platform and global supply chain infrastructure.

We create market access through franchising businesses that serve as master franchisees or licensing partners for brands entering new markets. Unlike traditional distribution partners that prioritize brick-and-mortar channels, our businesses leverage advanced ecommerce expertise to accelerate market entry while balancing online and offline channels to match local consumer behavior.

With 70% of global consumer growth driven by Asia, we're currently focused on enabling access to these high-potential markets. Our model offers brands significant advantages:

* Reduced market entry costs

* Broader consumer reach

* Faster testing and learning capabilities than traditional retail

* Local expertise with global backing

THE ROLE

Opptra is an AI-first company helping international brands expand into Asia — across India, GCC, and SEA — through franchising, licensing, and inventory-led partnerships. We move fast, build with intent, and run lean.

We're not hiring a PM and an engineer separately. We're looking for one person who can do both — talk to a warehouse ops lead, understand the problem they're describing, sketch a solution, and ship it within the same sprint. You will gather requirements, design flows, write code, deploy, and iterate in direct partnership with business and functional teams.

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WHAT YOU'LL DO

• Sit with business and ops teams, run discovery conversations, and translate fuzzy pain points into clear product specs — without a PM in between.
• Design lightweight AI-native solutions: agents, RAG pipelines, automation workflows, or internal tools — whichever solves the problem best.
• Build full-stack: React/Next.js frontends, Python or Node backends, BigQuery-connected APIs, and LLM integrations using OpenAI, Anthropic, or open-source models.
• Deploy and maintain your own work — CI/CD, monitoring, iteration — not hand it off to someone else to ship.
• Iterate in the open: share weekly updates with stakeholders, incorporate feedback quickly, and kill features that don't work without ego.
• Participate in the AI roadmap — you'll have a real say in what gets built next, and why.

THE SIX PILLARS OF THIS ROLE

• GATHER: Discovery, stakeholder interviews, translating ops problems into product requirements.
• BUILD: Full-stack engineering with AI components — not just the API call, but the whole product.
• SHIP: Deploy to production, instrument for observability, make it usable for non-technical users.
• ITERATE: Fast feedback loops with real users; improve ruthlessly based on evidence, not opinion.
• PARTNER: Embedded with business functions — not siloed in a separate tech team.
• OWN: Full accountability from problem definition to outcome, including what your AI systems do overnight.

TECHNICAL DEPTH WE EXPECT

• AI / LLM. You build with LLMs — not just use them. You understand prompt design, model selection tradeoffs, RAG architecture, agent orchestration, and how to evaluate AI output quality.
• Frontend. React or Next.js, component design, data-dense UIs (dashboards, tables, filters) — you build interfaces that non-technical users actually want to use.
• Backend. REST APIs (Python / Node), database design, BigQuery or similar, event-driven patterns, and integrations with third-party APIs (marketplace, logistics, catalog feeds).
• Deployment. Docker, basic CI/CD, cloud hosting — you can get your own code to prod without infra support.
• Data literacy. You can query, understand, and act on data — SQL fluency and a working instinct for metrics.

FOUNDER DNA — WHAT OPPTRA REWARDS

• Ships, doesn't just specify: Evidence of real products in production matters more than design docs or decks.
• Owns the full loop: If your AI system makes a bad decision at 2am, that's your decision. You monitor, you fix.
• Comfortable with discomfort: Scope isn't always clear. You figure it out rather than waiting for complete requirements.
• Learns in public: You share half-built things, ask for input, and improve — you don't disappear for a month and emerge with something.

WHAT WE'RE LOOKING FOR: STRONG PREFERENCE

✓ Full-stack engineering

✓ Product sensibility

✓ Requirements gathering

✓ LLM / AI-native building

✓ Shipped to real users

✓ RAG or agents hands-on

✓ Comfortable with ambiguity

✓ 2–7 years in product & tech

→ E-commerce / marketplace domain

→ India / GCC / SEA context

→ Startup experience

→ n8n / LangGraph / Cursor

→ BigQuery / dbt

→ Built solo products