Top Tech Jobs & Startup Jobs

The Finance Operations Lead will oversee customer billing, collections, finance processes, and improve operations through automation. They will implement workflows and maintain customer service standards while collaborating with accounting teams.

Design and implement agentic AI workflows and prototypes on the Netomi platform, integrate generative AI with APIs and cloud services, craft prompts and orchestration chains, partner with sales to scope solutions, present technical designs to stakeholders, and feed customer insights into product and engineering.

Lead discovery with enterprise customers to design and deploy agentic AI solutions. Define architectures, integration blueprints, workflows, guardrails, and analytics. Own integration design, validate behavior with QA, guide deployments, train stakeholders, and drive reusable templates and continuous improvement across cross-functional teams.

Lead product strategy and roadmap for autonomous conversational agents, translating enterprise needs into technical requirements. Partner with research, engineering, QA, and delivery to define agent reasoning, tool use, observability, failure recovery, and human handoffs. Establish telemetry, evaluation criteria, and release cadences; run post-release learning and cross-functional alignment to deliver reliable, production-grade agent capabilities at enterprise scale.

Design, optimize, test, and benchmark prompts and agent tool descriptions to improve AI performance. Collaborate with Customer Success and Data Science, automate evaluation and testing, document prompt practices, and research new NLP and model-specific prompting strategies.

Design, build, and maintain scalable Java/Spring Boot backend services and APIs. Own integrations, optimize performance and observability, implement messaging/caching, write tests, and deliver reliable microservices in a fast-paced startup environment.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.

As a Senior Data Analyst, you will analyze large datasets to support machine learning models, optimize AI implementations, and drive performance improvements. Responsibilities include data analysis, client onboarding, and working with cross-functional teams to enhance AI solutions.

Lead global quality engineering and testing practices for AI-driven SaaS products, enhance automation, and ensure high-quality releases through effective strategies and collaboration.

The role involves testing AI conversational products, improving quality assurance processes, and providing feedback for enhancing model accuracy.