Trainee Junior Mern Stack Developer Jobs in Alabama

ABOUT THE ROLE

We're building intelligent product search that understands intent, learns from behavior, and gets smarter over time. As a SeniorFull StackEngineer on the ML/AI Search team, you'll design and buildboththefrontend and backendsystems that power product discovery for millions of industrial buyers-from scalable retrieval pipelines,APIs, and Frontendinterfaces that make AI accessible.

This isn't a research role. You'll own the full lifecycle: prototyping ideas, shipping production-grade services on GCP, and iterating based on real user data. Strong Pythonand Reactengineeringisthe foundation-if you also bring experience in search systems, vector databases, or Elasticsearch, you'll hit the ground running from day one.

WHAT YOU'LL DO

Build & Ship Search and AI-Powered Systems

• Design, develop, and deploy production Python services end-to-end-from retrieval and ranking pipelines through client-facing APIs.

• Build and integrate ML inference pipelines: embedding models, transformer-based classifiers, LLM-powered query understanding, and reranking services.

• Develop event-driven, real-time architectures using GCP services-Cloud Run, Pub/Sub, GKE, Cloud Functions.

• Write clean, well-tested, observable Python backends; own your services through deployment, monitoring, andon-call

• Drive frontend architecture decisions, establishing development standards, and creating reusable component libraries.

Contribute to Search Infrastructure

• Work alongside the Search Architect and ML Architect to implement hybrid retrieval systems combining keyword search, dense vector similarity, and reranking.

• Build and maintain Elasticsearch indexing pipelines, query services, and relevance tuning tooling.

• Integrate vector databases (Pinecone,Weaviate, FAISS or similar) into retrieval workflows-even if this is new territory, you'll learn fast.

• Instrument search pipelines with meaningful metrics: CTR, zero-result rate, latency-feeding the team's A/B experimentation loop.

• Build clean, responsive, and production-ready interfaces from wireframes or Figma designs.

Own the Engineering Bar

• Champion CI/CD, observability, testing, and infrastructure-as-code as non-negotiables, not afterthoughts.

• Lead design sessions with Engineers and Architects; translate product requirements into clean, maintainable technical solutions.

• Participate in code reviews and knowledge-sharing-actively raising the team's collective skill level.

WHAT YOU BRING

Must-Haves

• Strong Pythonand Reactfoundation:6+ years of professional backend or full-stack engineering experience with a deep Python/React (e.g.,Next.js, Vite.js, Remix.js, Gatsby.js)focus-async patterns, type annotations, testing, and production-grade service/componentdesign.

• Cloud-native experience:Proven experience designing and deploying cloud-native applications (

GCP strongly preferred; AWS or Azure considered).

• Hands-on experience building resilienthigh throughputmicroservices and RESTful/gRPCAPIs.

• Solid understanding of containerization (Docker), orchestration (Kubernetes), and serverless paradigms.

• Strong grounding in SOLID design principles and software craftsmanship.

• Good communicator who thrives in cross-functional, agile teams alongside ML engineers, architects, and product owners.

• Comfort using AI tools to accelerate development throughput.

• Strong experience of using and managingMonorepos

• Strong understanding of relational (e.g.,PostgreSQL, MySQL, Oracle) and non-relational databases (e.g., MongoDB, DynamoDB).

• Mentorship:Provide guidance and technical knowledge sharing to mid-level and junior developers.

Strongly Preferred - Search & ML

You don't need all of these on day one-but the more you bring, the faster you'll contribute:

• Search systems:Experience with search platforms:

Elasticsearch, OpenSearch,Solr, orAlgolia-index management, query DSL, relevance tuning.

• Vector search:Familiarity with vector search concepts and tooling:

embeddings, approximate nearest neighbor (ANN), FAISS, Pinecone,Weaviate, or similar.

• Exposure to ML/AI patterns: RAG pipelines, LLM integration, prompt engineering, or fine-tuning workflows.

• Experience with AI orchestration frameworks such asLangChain,LangGraph, or Google ADK.

• Infrastructure-as-code experience (Terraform,Pulumi,OpenTofu) and mature CI/CD pipeline ownership.

WHO YOU ARE