Top Entry Level Artificial Intelligence Software Engineer Jobs

Design, develop, and implement cloud applications and automated tests on Microsoft Azure using C#/.NET and full-stack technologies. Evaluate architecture, scalability, reliability, performance, and maintenance risks; make technical trade-offs; design comprehensive test coverage; troubleshoot issues; and deliver moderately complex features. The role collaborates with software engineering teams while working independently on larger assignments and using Agile and AI-assisted development practices.

Own customer outcomes for Gasworks, an agentic platform. Deploy and operate the product in customers’ repositories, CI systems, clouds, and identity environments; debug distributed systems; write customer-driven fixes and integrations; and turn deployments into repeatable onboarding playbooks. The role combines software engineering, customer-facing implementation, product feedback, technical documentation, and daily use and verification of coding agents. Some customer travel is required.

Build customer-specific integrations, dashboards, data pipelines, and data transformations for the Faros platform. Work directly with customers to understand technical challenges, support evaluations and proofs of concept, communicate solutions, and iterate based on feedback. Collaborate with senior engineers and account executives, identify recurring customer needs, influence product roadmaps, and progressively assume greater ownership while using AI-powered development tools.

Build and ship AI-native systems for enterprise customers across the full product lifecycle, from requirements gathering and research through experimentation, implementation, and iteration. The role includes customer engagement, product direction, and hands-on development across frontend, backend, and full-stack systems. Candidates should demonstrate strong engineering fundamentals, product judgment, experience building agentic systems, and an understanding of AI system behavior, failure modes, and improvement.

Develop and evaluate new AI and HCI product concepts through hypotheses, prototypes, experiments, and user testing. Build model harnesses, improve memory and context retrieval, and collaborate with ML researchers to connect product and model feedback. Determine which ideas should advance into products, document unsuccessful experiments, and own implementation and direction for successful product areas.

Build and improve HUD’s platform and marketplace for RL training data and evaluations. The Product Engineer will identify user friction, define priorities, design prototypes, and ship full-stack product experiences. Responsibilities include improving agent-run and evaluation workflows, building frontend and backend functionality for onboarding and environment submission, and using user feedback and product signals to iterate. The role requires close collaboration with product, design, engineering, research, and go-to-market teams.

Lead the development of Ello’s growth-engineering function and ship end-to-end features across mobile, web, backend, and lifecycle channels. Identify growth opportunities, run experiments, define metrics, improve acquisition and retention journeys, and build analytics and experimentation systems. Collaborate across product, design, marketing, and engineering while using quantitative and qualitative insights to drive measurable user and business outcomes.

Build and improve a full-stack product that enables customers to manage AI agent workflows, including exception queues, reconciliation reviews, approvals, reporting, APIs, and agent SDK tools. The role involves frontend and backend development, real-time interfaces, workflow reliability, traceability, customer feedback, and polished user experiences. Engineers work in person with customers and a small founding team to shape product direction and solve ambiguous technical problems.

Lead and grow the platform engineering team while providing hands-on technical direction. Design and build scalable enterprise platform systems covering identity, access management, integrations, extensibility, reliability, security, compliance readiness, and operational excellence. Translate customer needs into technical deliverables, mentor engineers, and guide development in an ambiguous startup environment. AI agent or production LLM experience is beneficial.

Build and help lead Orpex, an AI workforce infrastructure startup. The role is intentionally flexible across engineering, product, technical leadership, and company operations. The hire will define their first 90-day ownership, work directly with the founder, establish engineering and hiring standards, and build the platform for AI-powered service companies. Prior startup founding, CTO, technical founding, product shipping, or service-business operating experience is expected.