AI Systems Engineer

AI Systems Engineer

Join Suffolk's AI Studio in Boston as an AI Systems Engineer, a hybrid role responsible for architecting and building both:

• The distributed systems backbone that powers enterprise-scale AI, and
• The agentic and LLM-driven capabilities transforming construction workflows

This role sits at the intersection of platform engineering and applied AI. You will design scalable APIs, event-driven services, and reliable infrastructure — while also implementing multi-model AI agents, retrieval pipelines, and AI orchestration frameworks that operate in real-world production environments.

You will help define how AI is built, deployed, observed, and scaled across Suffolk's national operations.

Responsibilities

AI & Agentic Systems Product Engineering & Deployment

• Design and implement production-grade RAG architectures
• Build and deploy multi-model AI agents leveraging AWS Bedrock and LLM providers (Claude, GPT, Llama, Titan, etc.)
• Implement dynamic model routing strategies based on task complexity, cost, and latency
• Develop multi-agent orchestration frameworks enabling collaborative workflows (planner, retriever, executor, summarizer)
• Design safe tool invocation patterns and guardrails for enterprise AI agents
• Optimize inference pipelines for cost, performance, and reliability
• Implement evaluation frameworks to measure model performance, hallucination rates, and response quality
• Design fallback and degradation strategies for model outages or latency spikes

Distributed Systems & Platform Architecture

• Architect and evolve service-oriented and event-driven systems supporting AI workloads
• Design REST/GraphQL APIs with clear versioning, authentication, and backward compatibility strategies
• Implement asynchronous processing pipelines using queues, event buses, and workflow orchestration
• Ensure reliability through idempotent consumers, retry strategies, circuit breakers, and dead-letter queues
• Make informed tradeoffs between relational, NoSQL, and vector storage systems
• Build services that are observable, traceable, and production-ready
• Define and document architectural standards for AI platform services
• Implement LLMOps: cost monitoring, latency optimization, usage analytics, and model versioning
• Enforce security, governance, and access standards in line with enterprise policies

Collaboration & Technical Leadership

• Work closely with product managers, site AI engineers, and data scientists to iterate rapidly in Agile sprints
• Communicate technical progress clearly to non-technical stakeholders; contribute to internal AI playbooks and templates

Qualifications

• 6+ years of professional software engineering experience (not including vibe coding)
• Demonstrated experience designing distributed or service-oriented systems in production
• Strong backend engineering skills in Python, and at least one of Java, NodeJS, Rust or Kotlin
• Experience building and deploying event-driven architectures (SNS/SQS, Kafka, EventBridge, etc.)
• Experience integrating LLMs into production systems (Bedrock, OpenAI, Anthropic, etc.).
• Hands-on experience with RAG pipelines, vector databases and building multi-agent AI systems
• Deep understanding of:
• Distributed system failure modes
• API lifecycle management
• Concurrency and consistency tradeoffs
• LLM cost, latency, and reliability constraints
• Tuning AI Agents for accuracy and performance

Preferred

• Experience building internal AI platforms or shared infrastructure
• Exposure to large-scale SaaS or mission-critical systems
• Experience designing multi-agent or orchestration frameworks
• Experience with Databricks Lakehouse architecture
• Prior experience in construction, manufacturing, or operational industries

What Makes This Role Unique

This role requires equal fluency in:

• Designing distributed systems that scale
• Engineering intelligent agentic systems that reason

We are looking for engineers who understand that production AI is not just about model quality and prompt engineering — it is also about the systems that deliver, monitor, and evolve those models and agents safely at scale.

Working Conditions

While performing the duties of this job, the employee is regularly required to sit for long periods of time; talk or hear; perform fine motor, hand and finger skills in the use of a keyboard, telephone, or writing. The employee is frequently required to stands; walk; and reach with arms and/or hands. Specific vision abilities include close vision, distance vision, depth perception and the ability to adjust focus. The employee will spend their time in an office environment with a quiet to moderate noise level. Job site walking.

EEO Statement

Suffolk provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, pregnancy or maternity, national origin, citizenship, genetic information, disability, protected veteran, gender identity, age or any other status protected by law. This policy applies to recruiting, hiring, transfers, promotions, terminations, compensation, benefits, and all other terms and conditions of employment. Suffolk will not tolerate any unlawful discrimination toward, or harassment of, applicants or employees by anyone at Suffolk, or anyone working on behalf of Suffolk.

Compensation Information

Where required by law, pay ranges can be found in Suffolk's job postings. Base Salary for this position is just one component of Suffolk's total rewards package for employees. Actual salaries may be based on several factors including, but not limited to, a candidate's skill set, experience, education and other qualifications. Suffolk offers a comprehensive benefits package as part of its overall total rewards strategy. Salary ranges are reviewed regularly to reflect market trends.