About This Job

Axiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows.

Our mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.

We aim to revolutionize hardware design and simulation in these industries and are building a team of highly motivated professionals to bring these innovations from research into commercial products.

Position Overview

As Staff Software Engineer (Backend), you will set the technical direction for our backend platform and drive the systems that power an AI-native product at scale. This is a hands-on, T-shaped role with a deep backend specialization: you'll spend roughly 70% of your time writing and reviewing backend code, 20% on architecture and technical strategy, and 10% contributing to frontend work when needed.

You operate at the intersection of backend engineering, AI infrastructure, and platform reliability, making the foundational decisions that let every other engineer ship faster, safer, and cheaper.

You will:

Write and ship backend code daily — this is first and foremost a hands-on engineering role

Own the technical strategy for backend systems and AI infrastructure

Lead cross-functional initiatives spanning backend, AI, infra, and frontend

Design and evolve foundational platforms (model routing, agent runtime, persistence, observability)

Drive engineering excellence through RFCs, standards, and architecture reviews

Contribute to frontend development when needed, collaborating with frontend engineers on integration points

Multiply the team through mentorship and force-multiplier code (frameworks, internal libraries, shared patterns)

Be the technical owner of production reliability: incident response, performance, cost, security

Key Responsibilities

1. Technical Strategy & Architecture

Set the 12–24 month technical roadmap for backend systems with the Head of Engineering / Lead Software Engineer

Author RFCs and design documents that shape the engineering organization

Make build-vs-buy decisions on critical platform components (model routing, vector DBs, queues, eval pipelines)

Design for scale, multi-tenancy, and compliance readiness

Drive architecture reviews and ensure technical consistency across squads

1. Platform & Infrastructure

Own foundational systems: conversation persistence, observability stack, and core platform services

Lead cost-optimization initiatives (caching strategies, batching, resource budgets)

Establish SLOs and drive incident response, postmortems, and durable fixes

Partner with infra on the deployment story (Cloud Run, Cloud SQL, VPCs, multi-region)

Drive security and compliance (auth, secrets, data residency, audit trails)

1. AI Systems

Collaborate with the AI team to integrate LLM-powered features into backend services

Design clean abstraction layers for model providers, enabling routing and fallback

Contribute to patterns for prompt management, evaluation, and regression testing

Stay informed on emerging AI infrastructure trends and help evaluate build-vs-buy decisions

1. Engineering Excellence

Set and enforce coding standards, review templates, and testing practices

Drive measurable quality improvements (p95 latency, error budgets, test coverage, infra cost)

Identify systemic issues and design durable fixes, never one-off patches

Build internal frameworks and libraries that raise the velocity of every other engineer

1. Leadership & Mentorship

Mentor senior engineers and help them grow toward staff

Lead technical interviews and define the engineering bar

Represent backend engineering in cross-functional planning

Communicate trade-offs clearly to product, leadership, and external stakeholders

Coach the team on debugging, performance work, and incident response

Key Requirements

10+ years of backend development experience, with 2+ in a staff/principal/lead role

Documented technical leadership: led architecture for multi-team systems, authored RFCs adopted org-wide

Deep Python expertise: FastAPI, async, type system, profiling, internals

Distributed systems intuition: caching, queues, eventual consistency, idempotency, backpressure

Production-grade Databases: query optimization, schema migrations, partitioning, connection pooling, ORMs (SQLAlchemy)

Cloud platform mastery: GCP (Cloud Run, Cloud SQL, GCS, VPCs, IAM, Auth0) designing, not just consuming

Comfort working alongside AI workloads: basic familiarity with LLM API integration patterns; willingness to learn and support AI infrastructure as needed

Systems thinking: incident response, observability, SLO design, capacity planning

Force-multiplier mindset: designed and shipped frameworks/libraries adopted by other engineers

Excellent technical communication: RFCs, design docs, architecture reviews, async writing

Nice-to-Have

Experience with LLM integration in production (Anthropic, Google, OpenAI, Vertex AI)

Familiarity with agent frameworks (Pydantic AI, LangGraph, FastMCP) or similar

Frontend experience with React, Angular, or Vue — ability to contribute to UI when needed

Scaling an AI product from 0 → 1 and 1 → 10

Authoring open source or internal frameworks adopted by other teams

Performance-critical Python (Rust/Go interop, async tuning, native extensions)

Multi-region / multi-tenant architecture

Security/compliance background (SOC2, GDPR, secret management)

Infrastructure as code (Terraform), GitOps, platform engineering

Tech Stack

Current Stack:

Backend: Python, FastAPI, SQLAlchemy, Pydantic AI, FastMCP, Alembic

Databases: PostgreSQL, Redis (caching)

APIs: REST, WebSockets, SSE, MCP

AI/ML: Anthropic Claude, Google Gemini, OpenAI, Vertex AI Model Garden, Mistral OCR

Cloud: Google Cloud Platform (Cloud Run, Cloud SQL, GCS, VPCs, Auth0)

Infrastructure: Terraform, Docker

CI/CD: GitHub Actions

Observability: Logfire, Sentry, OpenTelemetry

Testing: pytest, pytest-asyncio, pytest-cov

Work model & location expectations:

Team work model: Preferred hybrid from our Boston office; remote arrangement may be considered.

Primary location: Boston, US

Why join us?

At Axiomatic_AI, you will be working on technology that drives innovation in AI for scientific and engineering applications in line with our 30X30 mission.

This is your opportunity to contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions. Consequently, see those ideas commercialized into products that will shape the future of hardware and computing, while collaborating with a global team of engineers and AI specialists.

We believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI, with focus on formal consistency. If you're ready to take your expertise in artificial intelligence and physics to the next level, we want to hear from you!

Worried about not meeting every qualification? Studies show that women and people of color are less likely to apply for jobs unless they meet every listed requirement. At Axiomatic-AI, we are dedicated to creating a diverse, inclusive, and authentic workplace. If this role excites you but your background doesn’t perfectly match every qualification, we still encourage you to apply. You could be the perfect fit for this position or another opportunity with us.

Position Name

Staff Software Engineer (Backend)