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Backend Ai Engineer Jobs in Roxbury, MA (NOW HIRING)

Role Join Suffolk's AI Studio in Boston as a core engineer transforming how AI powers construction ... Build APIs, backend services, and agentic workflows using Python, FastAPI, LangChain, and AWS SDKs.

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

As a Senior AI Engineer, you will design and build scalable backend systems and user experiences that power AI products and solutions, collaborating closely with product managers, machine learning ...

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

As a Senior AI Engineer, you will design and build scalable backend systems and user experiences that power AI products and solutions, collaborating closely with product managers, machine learning ...

AI Engineer

Boston, MA · On-site

$107K - $222K/yr

Role Join Suffolk's AI Studio in Boston as a core engineer transforming how AI powers construction ... Build APIs, backend services, and agentic workflows using Python, FastAPI, LangChain, and AWS SDKs.

AI Product Engineering & Deployment * Translate product requirements and user stories into ... Build APIs, backend services, and agentic workflows using Python, FastAPI, LangChain, and AWS SDKs.

AI Engineer Client: Plymouth Rock Assurance Location- Boston, MA 4 days/week onsite(Only Locals ... Experience building APIs, MCPs, and scalable backend services. * Experience with Claude Code, Codex ...

Senior AI Engineer

Boston, MA · On-site

$113K - $155K/yr

Orchestrate AI workflows using tools like LangChain, LlamaIndex, or similar frameworks, integrating them with product APIs and backend services. * Drive prompt engineering and iteration - refine ...

Principal Engineer (Backend / Platform)About Us We are a Cambridge, MA-based rapidly scaling Generative AI startup. Our platform enables thousands of AI Agents to "think" and cooperate for hours to ...

AI Engineer (Hybrid)

Boston, MA · Hybrid

$130K - $190K/yr

... back end. RAG Pipelines & LLMOps: Design and operate retrieval‐augmented generation (RAG ... Qualifications 4+ years in AI engineering, data science, or ML‐focused software engineering.

AI Engineer (Hybrid)

Boston, MA · Hybrid

$130K - $190K/yr

... back end. RAG Pipelines & LLMOps: Design and operate retrieval‐augmented generation (RAG ... Qualifications 4+ years in AI engineering, data science, or ML‐focused software engineering.

Develop full-stack AI applications with both frontend and backend components * Optimize model ... Expert-level Python programming skills * Strong proficiency in JavaScript and Java * Deep ...

AI Engineer

Boston, MA · On-site

$100 - $130/hr

Experience developing scalable APIs, backend services, and enterprise AI integrations while ... You will collaborate with engineering, data, and business stakeholders to design scalable AI ...

AI Engineer

Boston, MA · On-site

$65 - $80/hr

Experience developing scalable APIs, backend services, and enterprise AI integrations while ... You will collaborate with engineering, data, and business stakeholders to design scalable AI ...

Senior AI Engineer - Customer Agent

Boston, MA · On-site

$113K - $155K/yr

They are seeking a Senior AI Engineer to design and build scalable backend systems for their AI products and AI agent solutions, collaborating closely with product managers, machine learning ...

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Backend Ai Engineer information

See Roxbury, MA salary details

$65.7K

$160.3K

$216K

How much do backend ai engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for backend ai engineer in Roxbury, MA is $160,250.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,600.00 and $186,700.00 per year, depending on experience, location, and employer.

What is a Backend AI Engineer?

A Backend AI Engineer is a software engineer who specializes in building and maintaining the server-side infrastructure for artificial intelligence applications. Their work involves designing APIs, integrating machine learning models, managing databases, and ensuring efficient data flow between systems. They collaborate with data scientists and frontend developers to deploy AI models at scale and make them accessible through robust backend services. Key skills for this role include programming (often in Python, Java, or similar languages), cloud computing, and knowledge of AI frameworks.

What are the key skills and qualifications needed to thrive as a backend AI engineer?

To thrive as a Backend AI Engineer, you need strong programming skills (especially in Python or Java), a deep understanding of algorithms and data structures, and a background in computer science or related fields. Familiarity with AI/ML frameworks (like TensorFlow or PyTorch), RESTful APIs, databases, and cloud platforms is typically expected, along with relevant certifications. Exceptional problem-solving abilities, teamwork, and effective communication are soft skills that distinguish top performers. These competencies are crucial for designing robust, scalable AI solutions that integrate seamlessly with backend systems and drive innovation.

What are some common challenges backend AI engineers face when deploying machine learning models to production?

Backend AI Engineers often encounter challenges such as ensuring model scalability, maintaining low latency, and handling diverse data inputs during deployment. Integrating models into existing backend systems can also require careful consideration of APIs, security, and resource management. Additionally, monitoring model performance and updating models with new data are ongoing responsibilities that require close collaboration with data scientists, DevOps, and product teams.

What is the difference between Backend Ai Engineer vs Data Scientist?

AspectBackend Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; knowledge of programming, AI frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI models, integrates AI into backend systems, collaborates with software teamsAnalyzes data, builds models, interprets data insights, collaborates with business teams
Industry UsageTech companies, AI startups, software firmsResearch institutions, tech companies, finance, healthcare
Common Search/ComparisonYesYes

While both roles involve working with AI and data, Backend Ai Engineers focus on integrating AI models into backend systems and developing scalable AI solutions. Data Scientists primarily analyze data, build predictive models, and generate insights. The roles often overlap in skills and tools but differ in their core focus—system integration versus data analysis.

What are popular job titles related to Backend Ai Engineer jobs in Roxbury, MA?

For Backend Ai Engineer jobs in Roxbury, MA, the most frequently searched job titles are:

What cities near Roxbury, MA are hiring for Backend Ai Engineer jobs?

Cities near Roxbury, MA with the most Backend Ai Engineer job openings:

Infographic showing various Backend Ai Engineer job openings in Roxbury, MA as of August 2026, with employment types broken down into 71% Full Time, and 29% Contract. Highlights an 100% In-person job distribution, with an average salary of $160,250 per year, or $77 per hour.

Staff Software Engineer (Backend)

Axiomatic-AI Inc.

Boston, MA • On-site

$130 - $180/hr

Other

Re-posted 18 days ago


Job description

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 a 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.

  • 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
2. 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)
3. 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
  • 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
  • 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
  • Distributed systems intuition: caching, queues, eventual consistency, idempotency, backpressure
  • Production‑grade Databases: query optimization, schema migrations, partitioning, connection pooling, ORMs (SQLAlchemy)
  • 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
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)
  • Security/compliance background (SOC2, GDPR, secret management)
  • Infrastructure as code (Terraform), GitOps, platform engineering
Current Stack
  • Backend: Python, FastAPI, SQLAlchemy, Pydantic AI, FastMCP, Alembic
  • Databases: PostgreSQL, Redis (caching)
  • APIs: REST, WebSockets, SSE, MCP
  • Infrastructure: Terraform, Docker
  • CI/CD: GitHub Actions
  • Observability: Logfire, Sentry, OpenTelemetry

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

Primary location: Boston, 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!

As set forth in Axiomatic_AI’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

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