Top Tech Jobs & Startup Jobs in New Orleans, LA

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.

Lead and scale a strategic sales channel for an LTL logistics company, building high-performance sales teams, aligning commercial strategy with operations, driving growth through CRM and Power BI analytics, and executing aggressive performance and travel-heavy sales plans.

Sell and retain national LTL accounts by prospecting, pricing, and building relationships across account hierarchies. Collaborate with operations, resolve customer issues, complete sales reporting, assist with collections, and support team goals. Heavy customer-facing travel and territory management with emphasis on sales, negotiation, and confidentiality.

Sell LTL services to multi-location corporate accounts, generate new business, retain and grow existing accounts, develop pricing, collaborate with operations, handle customer inquiries, assist collections, complete sales reporting, and travel extensively for client visits and prospecting.

Summer internship to build production-facing realtime intelligence for a mobile app that optimizes campus quest participation. Design context-aware quest logic, detect stalls/drop-offs, suggest micro-actions, instrument evaluation loops, and ship components on top of existing realtime systems to improve behavioral outcomes like IRL quest completion and retention.

Develop and execute multi-channel customer acquisition strategies (SEO, SEM, email, social) to attract nonprofit clients. Analyze campaign and customer data to optimize ROI, identify decision-makers, generate leads, and coordinate hand-offs to client services and finance. Collaborate with partners, sales, and marketing to align acquisition efforts with firm goals.

Build and scale backend systems for a high-traffic donor CRM and payments platform. Own performant SQL and realtime querying, optimize payment flows, implement AI agents, and collaborate across product and design to ship resilient, production-grade features at scale.

Design, build, and maintain Node.js backend services and APIs; integrate with front-end; optimize for performance and scalability; manage PostgreSQL and MongoDB databases; follow TDD and agile practices; perform code reviews and collaborate within a remote engineering team.

Build and ship end-to-end product features across frontend, backend, and agent-driven workflows; design scalable architectures; improve developer velocity, tooling, and product quality; apply AI-native engineering practices; collaborate on core product experience and execute high-leverage work with strong ownership.

Own strategic customer relationships and lead deployment of AI workflows into supplier operations. Map customer SOPs and data sources, identify high-ROI AI opportunities, translate needs into product and implementation requirements, drive adoption, partner with product/engineering, build playbooks, track value, and surface expansion opportunities across global teams.

Partner with small-business clients to manage full-cycle recruiting: source, screen, interview, and hire candidates. Collaborate with hiring managers, document recruiting plans and timelines, coordinate interviews and offers, and provide consultative recruiting and HR support on a fractional, part-time basis.

Drive awareness and education of Dose products to healthcare professionals via outbound/inbound calls, emails, and virtual meetings. Qualify leads, manage a pipeline in CRM, collaborate cross-functionally, hit sales targets, and maintain product and competitive knowledge.

Build and own user-facing features and core platform architecture across frontend, backend, and ML pipelines. Integrate AI workflows (LLMs, embeddings) for curriculum generation and automated evaluation. Manage end-to-end development: requirements, design, implementation, CI/CD, testing, observability, and iteration while collaborating with product, design, ML, and customer teams.

Design, build, and productionize LLM-powered systems (adaptive content, tutors, evaluators) and AI pipelines (RAG, embeddings, fine-tuning). Prototype and optimize models across modalities, define AI safety/evaluation/observability practices, and collaborate with product and engineering to measure learner outcomes and iterate.