AI Solutions Engineer (Entry-Level)
Role details
Job location
Tech stack
Job description
As a Junior AI Solutions Engineer, you will join our Enterprise AI team to accelerate Proxima Fusion's operational and technical workflows. You will be responsible for identifying, designing, and deploying AI-driven automations that eliminate bottlenecks across the organization. This is a role for a builder who thrives in an agile environment and is excited about applying the latest AI technology to solve real-world startup challenges at high speed., * Design and implement sophisticated automation architectures using tools like n8n, LangGraph and Python, integrating LLM capabilities into the core of Proxima's business and technical operations.
- Orchestrate our ecosystem by integrating AI workflows with existing data sources and tools, including Google Drive, Slack, project management software, and meeting infrastructure.
- Deploy and manage AI-driven microservices on Google Cloud Platform (GCP), utilizing Cloud Run, Vertex AI, and Vector Databases.
- Develop and optimize agentic workflows that leverage REST APIs, MCP (Model Context Protocol), and multi-modal Generative AI (Text, Image, and Video).
- Collaborate with the Enterprise AI Team to translate high-level system designs into functional prototypes, validating results directly with internal stakeholders.
- Integrate with our Software Development and Dev-Platform team to ensure all AI deployments follow Proxima's infrastructure and coding best practices
Requirements
- A High-Agency Builder: You prioritize shipping functional, high-impact prototypes and have a proven "builder" mindset when it comes to solving complex problems with simple solutions.
- Collaborative & Mission-Driven: You choose mission over ego, working seamlessly across a diverse team of physicists, engineers, and ops. You are an excellent communicator who can bridge the gap between technical AI tools and the needs of non-technical colleagues.
- Technically Proficient: You have a solid foundation in Python and a deep understanding of LLM APIs, prompt engineering, and the current GenAI ecosystem.
- Infrastructure-Aware: Familiar with Linux, Docker, and cloud-native environments (ideally GCP). You understand how to interact with and design clean RESTful APIs.
- Continuous Learner: You are obsessed with the "state-of-the-art" and are likely the first person to experiment with new AI models or frameworks the day they are released.
- Proactive & Pro-Feedback: You go above and beyond to see things through. You see feedback as a gift and iterate fast based on user validation.
- Startup-Ready: You thrive in high-paced environments characterized by high ambiguity and rapid iteration cycles.
INTERVIEW PROCESS
- Recruiter Interview (30-60 min)
- Technical Screening (30 min)
- Technical Panel (3x60 min)
- CEO call (30 min)