Jobs at NinjaTech AI

Own and build NinjaTech’s partner enablement program for Infosys. Develop onboarding, training, certification, collateral, demos, implementation playbooks, and a partner knowledge base. Equip Infosys sales, solutions, and delivery teams to independently position, sell, deploy, and support SuperNinja. Track enablement and pipeline KPIs, run joint go-to-market activities, and collaborate with Product, Sales, and Solutions Engineering to keep partner materials current.

Build and deploy custom AI agent workflows for enterprise customers, integrating NinjaTech with data sources, identity systems, CRMs, ticketing platforms, and internal APIs. Lead technical discovery, architecture, security reviews, customer adoption, and expansion. Develop prompts, tools, guardrails, and automations; troubleshoot production deployments; communicate with executives and frontline users; and provide feedback or reusable components to core engineering.

Owns NinjaTech AI’s marketing function from the ground up, including positioning, product launches, demand generation, content, PR, social media, website optimization, sales enablement, events, partnerships, analytics, and marketing operations. The role requires a hands-on B2B enterprise marketer who can translate complex AI technology for technical buyers, build pipeline, manage campaigns and channels, and establish scalable marketing processes.

Own product management across SuperNinja and AI Workforce, including product narrative, use-case prioritization, customer launches, onboarding, adoption metrics, feedback-driven iteration, and scalable launch playbooks. Partner with the CEO, Chief Science Officer, sales, customers, and engineering to drive product adoption, define requirements, support enterprise deployments, and establish a repeatable product operating model.

The Full Stack Software Engineer will develop, integrate, and deploy AI technologies, focusing on building scalable web applications and ensuring a great user experience.

Lead applied research and engineering to develop, train, optimize, and deploy agentic AI and LLM systems. Build large-scale multi-GPU training and inference pipelines, design datasets, run experiments and A/B tests, improve NLU/NLG and speech capabilities, and ship robust production ML systems in Python and Rust.

Own monetisation and activation end-to-end: subscriptions, paywalls, billing, onboarding and first-use activation. Build analytics and experimentation foundations (events, funnels, A/B tests). Integrate with payment providers and handle failure modes (declines, webhooks, disputes). Drive data-informed experiments to improve funnel and revenue.

Own and build enterprise identity and tenancy: implement SAML/OIDC federation and SCIM provisioning, design self-serve tenancy (orgs, seats, roles, entitlements), create audit/admin surfaces (access logs, session policy, de-provisioning), and partner on rollouts to ensure frictionless enterprise deployments.