AI Systems Engineer

AI Systems EngineerJoin 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, andThe agentic and LLM-driven capabilities transforming construction workflowsThis 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.ResponsibilitiesAI & Agentic Systems Product Engineering & DeploymentDesign and implement production-grade RAG architecturesBuild 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 latencyDevelop multi-agent orchestration frameworks enabling collaborative workflows (planner, retriever, executor, summarizer)Design safe tool invocation patterns and guardrails for enterprise AI agentsOptimize inference pipelines for cost, performance, and reliabilityImplement evaluation frameworks to measure model performance, hallucination rates, and response qualityDesign fallback and degradation strategies for model outages or latency spikesDistributed Systems & Platform ArchitectureArchitect and evolve service-oriented and event-driven systems supporting AI workloadsDesign REST/GraphQL APIs with clear versioning, authentication, and backward compatibility strategiesImplement asynchronous processing pipelines using queues, event buses, and workflow orchestrationEnsure reliability through idempotent consumers, retry strategies, circuit breakers, and dead-letter queuesMake informed tradeoffs between relational, NoSQL, and vector storage systemsBuild services that are observable, traceable, and production-readyDefine and document architectural standards for AI platform servicesImplement LLMOps: cost monitoring, latency optimization, usage analytics, and model versioningEnforce security, governance, and access standards in line with enterprise policiesCollaboration & Technical LeadershipWork closely with product managers, site AI engineers, and data scientists to iterate rapidly in Agile sprintsCommunicate technical progress clearly to non-technical stakeholders; contribute to internal AI playbooks and templatesQualifications6+ years of professional software engineering experience (not including vibe coding)Demonstrated experience designing distributed or service-oriented systems in productionStrong backend engineering skills in Python, and at least one of Java, NodeJS, Rust or KotlinExperience 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 systemsDeep understanding of:Distributed system failure modesAPI lifecycle managementConcurrency and consistency tradeoffsLLM cost, latency, and reliability constraintsTuning AI Agents for accuracy and performancePreferredExperience building internal AI platforms or shared infrastructureExposure to large-scale SaaS or mission-critical systemsExperience designing multi-agent or orchestration frameworksExperience with Databricks Lakehouse architecturePrior experience in construction, manufacturing, or operational industriesWhat Makes This Role UniqueThis role requires equal fluency in:Designing distributed systems that scaleEngineering intelligent agentic systems that reasonWe 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 ConditionsWhile 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 StatementSuffolk 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 InformationWhere 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.