Top Artificial Intelligence Software Engineer Jobs

As a Software Engineer, you will collaborate on designing, developing, and testing AI models, maintain production systems, and explore new techniques within a small, impactful team.

The role involves deploying AI solutions for customers, translating their needs into features, and collaborating with engineering teams to adapt products to specific environments.

As the first engineer, you will own the full stack, architect the next Omi SDK version, build prototypes, and shape product direction with direct collaboration with the founder.

Develop backend systems for AI agents, ensuring usability, reliability, and operability in production environments. Collaborate with AI team to integrate features and lead technical discussions.

Design and present end-to-end AI, automation, and decision-management solutions for government clients. Architect secure cloud and low-code integrations, lead technical discovery, build demos/POCs using HT Navigator AI, and support pre-sales, proposals, and client workshops to drive adoption and value.

The Staff Frontend Software Engineer will architect and build high-performance React/TypeScript applications, mentor engineers, and lead frontend technical initiatives for complex cyber operation data visualization.

Own and evolve core backend microservices for an AI inference platform: build production-grade APIs, multi-tenant SaaS features (auth, RBAC, billing), design OLTP/OLAP data models, collaborate on multi-cloud orchestration, ensure reliability/performance, and drive engineering quality through testing and CI/CD.

The LTE Engineer will work on development and testing, focusing on LTE protocol stack knowledge, TTCN3 script development, and network simulator development.

The Principal Software Engineering Manager will lead the design of the ad serving infrastructure and manage teams to ensure reliability, scalability, and integration of AI technologies in digital advertising.

Lead end-to-end customer implementations by building custom integrations, configuring and productionizing AI agents, developing backend solutions, translating vague requirements into technical specs, and creating internal tools to accelerate repeatable deployments. Work closely with founders and clients to ship robust systems quickly.