Senior Applied AI Engineer

Axiomatic_AI • Boston, MA

7h • Hybrid

About The Position

Axiomatic AI is developing AI systems that combine deep learning with formal logic and physics-based modeling to support human researchers in scientific and engineering workflows. Its mission is to achieve a 30-fold improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.

The Senior Applied AI Engineer bridges AI research and production software. The role partners with users, internal stakeholders, software engineers, AI developers, scientists, and specialists to identify valuable workflows and deliver dependable AI product capabilities. The engineer owns applied AI features through discovery, design, implementation, rollout, and iteration, while establishing practices that help the team develop, evaluate, deploy, and maintain AI systems safely and reproducibly.

The position is hybrid, based at the Boston office three days per week, with potential options for remote work. The company offers competitive compensation, stock options, access to advanced tools and expert collaborators, flexible work arrangements, and opportunities for professional growth and participation in the AI research community.

Requirements

• At least 7 years of software engineering experience, preferably with Python, and strong production ownership.
• Experience using LLMs and AI/ML in production, such as the OpenAI API, Hugging Face, LangChain, or similar tools, beyond prototypes.
• Strong software engineering fundamentals, including design patterns, code structure, testing practices, and code review habits.
• Cloud infrastructure experience with GCP, preferably Vertex AI, or AWS, including SageMaker.
• API and service development experience, such as FastAPI, REST, or asynchronous programming.
• CI/CD and DevOps experience with tools such as Docker, Terraform, and GitHub Actions.
• Experience with monitoring and observability.
• Experience deploying AI in an enterprise environment.
• Experience shipping data projects to real users.
• Ability to define and scope tasks independently, take initiative, and identify opportunities for improvement.
• Problem-solving mindset.
• Ability to collaborate with software engineers.

Nice To Haves

• Experience fine-tuning or training models.
• Familiarity with LangChain, Pydantic AI, or similar frameworks.
• Knowledge of prompt engineering and evaluation techniques.
• Experience with real-time inference and streaming responses.
• Background in data engineering or ML engineering.
• Understanding of RAG architectures.
• Contributions to open-source AI/ML projects.

Responsibilities

• Partner with users and internal stakeholders to identify high-impact workflows where AI can help.
• Own applied AI features end-to-end, from discovery and design through implementation, rollout, and iteration.
• Translate user feedback and behavior into technical requirements and pragmatic delivery plans.
• Design and implement LLM-powered product features, including agents, tools, prompting strategies, structured-output pipelines, and retrieval or tool integrations.
• Choose and evaluate models and approaches based on quality, latency, cost, privacy, context limits, and reliability.
• Develop prompt patterns, guardrails, fallbacks, and lightweight evaluations to prevent regressions and test failure modes.
• Document model decisions, trade-offs, AI infrastructure, and best practices.
• Write production-grade code with clear abstractions, strong API boundaries, appropriate typing, and consistent error handling.
• Define and enforce applied AI testing practices, including unit, integration, and golden or regression tests.
• Implement logging, tracing, and metrics to support debugging and iteration.
• Address reliability and security fundamentals, including rate limiting, safe input handling, and prompt-injection awareness.
• Collaborate with backend and software engineers to integrate AI capabilities into the product.
• Help AI developers productionize experiments and establish workflows from notebooks and test repositories through pull requests, staging, and production.
• Review code and pull requests, mentor AI developers, and promote maintainable software practices.
• Monitor, evaluate, and optimize AI and agentic workflows.
• Collaborate with specialists and scientists to bring their expertise into the AI product.
• Communicate and justify technical decisions clearly and concisely to colleagues and stakeholders.

Benefits

• Competitive compensation.
• Stock Options Plan.
• Access to state-of-the-art tools and collaborative opportunities with experts in artificial intelligence, physics, hardware, and electronic design automation.
• Flexible work arrangements in one of the company's offices, with potential options for remote work.
• Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed