About Opptra: Opptra () 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 backingThe RoleYou are the builder at the frontier — someone who thrives in the messy intersection of productvision, customer reality, and technical execution. You'll be embedded with brand operationsteams, marketplace partners, and regional warehouses — shipping AI agents and platforminfrastructure that directly impact P&L.This isn't /"pure/" engineering or /"pure/" product. You'll write production code and designworkflows. You'll debug data pipelines and negotiate API contracts with marketplace teams.You'll build pricing agents and train brand managers on how to supervise them.Key Outcomes: Agent-Led Merchandising Use CasesIdentify high-impact AI use-cases in overall merchandising operations (pricing, promotions, and assortment within category pods)Define “jobs to be done” for agents (e.g., Dynamic Markdown Strategist, Regional Price Optimizer, Inventory Allocation Advisor)Create Agent use-case canvases with flows, prompts, datasets, and measurable outcomesPOC Development & Prototyping Build no-code AI POCs using tools like LangChain, Flowise, or CrewAIDevelop and demo early agents (e.g., Pricing Validator, Assortment Gap Finder, Auto Bundler) in tools like Replit, Zapier, or n8nConnect GenAI agents with data sources (CSV, APIs, mock dashboards) to simulate decision-makingExperimentation & Feedback Loops: Run lightweight tests (manual A/Bs, sandbox trials) with category managers to validate agent valueCollect qualitative feedback on workflows, trust, and usabilityPrioritize agents that replace high-effort, low-creativity tasks Agent Integration ReadinessPrepare structured specs for successful POCs (flows, prompts, guardrails, integrations) to hand off to engineeringCollaborate with internal AI team to translate validated POCs intoscalable agent workflowsTrack “Time to POC → Time to Value” metrics to prioritize rolloutQualifications: Must Have3+ years of experience in product, category ops, growth, or ecommerce toolingFamiliarity with pricing and merchandising strategy in omnichannelenvironmentsExposure to AI tooling like GPT, Claude, LangChain, Pinecone, or FireworksCan build scrappy MVPs using Zapier, Make, Bubble, Streamlit, or FlowiseExperience working alongside engineers or agent builders to transition from POCto productionStrong Preference ForE-commerce experience: Worked at MarketplacesStartup experience: Early engineer (top 50) at a growth-stage startupAI/LLM projects: Built something with GPT-4, Claude, or open-source LLMs in productionCross-functional roles: Product engineer, technical PM, solutions engineer, implementationconsultantMust-Have Skills:Development: PyCharm, IntelliJ, VS Code for coding; Postman, GraphiQL for API testing.AI/ML Frameworks: TensorFlow, PyTorch, Hugging Face, Scikit-learn, LangChain, LlamaIndex.Generative AI: Fireworks.ai, Anthropic Claude, Google Gemini for automation and content.MLOps: MLflow, Kubeflow, SageMaker, Weights & Biases for model deployment and tracking.Data: PostgreSQL, MongoDB, DynamoDB, Redis; Pinecone, Weaviate for vector search.Infrastructure: AWS (Lambda, ECS, RDS), GCP, Terraform, Kubernetes for cloud ops.Monitoring: Prometheus, Grafana, Datadog, AWS CloudWatch for system health.Collaboration: Jira, Slack, Notion, Confluence for planning and communication.Product/Business (Understand Why, Not Just What)Can translate messy business requirements into working softwareUnderstand e-commerce metrics (conversion, AOV, margin, ROAS, inventory turns)Comfortable presenting technical work to non-technical stakeholdersApply through this link:
Job Title
Forward Deployed Engineer