Suffolk Construction
AI Engineer
Location:
Boston (US-MA-Boston)
Overview About Suffolk Suffolk is a national enterprise that builds, innovates and invests. It is an end‑to‑end business that provides value throughout the entire project lifecycle by leveraging its core construction management services with vertical service lines that include real‑estate capital investment, design, self‑perform construction services, technology start‑up investment (Suffolk Technologies) and innovation research/development.
Suffolk - America's Contractor - is a national company with more than $5.0 billion in annual revenue, 2,600 employees, and main offices in Boston (headquarters), New York City, Miami, West Palm Beach, Tampa, Estero, Dallas, Los Angeles, San Francisco, and San Diego. It serves clients in every major industry sector, including healthcare, life sciences, education, gaming, transportation/aviation, government, mission‑critical and commercial. Suffolk is privately held, led by founder, chairman and CEO John Fish, and is ranked #8 on ENR's list of "Top CM‑at‑Risk Contractors." Visit www.suffolk.com for more information.
At Suffolk, we believe that our total rewards program should offer you and your family the support you need when it matters most. The program provides employees with access to wide variety of options that can be personalized to support you and your loved ones physically, emotionally, and financially.
Benefits include competitive salaries, auto allowances and gas cards for certain roles, access to market‑leading medical and emotional and mental health benefits, dental and vision insurance plans, virtual care options for physical therapy and primary care, generous paid time off, 401k plan with employer match and access to expert financial resources, company‑paid and voluntary life insurance, tax‑deferred savings accounts, 10 backup daycare days each year, short‑ and long‑term disability, commuter benefits and more.
Role Join Suffolk's AI Studio in Boston as a core engineer transforming how AI powers construction management. Partner with Product Managers, Site AI Engineers and Data Engineers to solve pain points, redesign workflows and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking and more. Focus on building secure, scalable and high‑performance AI agents using modern technologies including AWS Bedrock and Databricks – shaping the backbone of Suffolk's "Construction Site of the Future."
Responsibilities AI Product Engineering & Deployment
Translate product requirements and user stories into production‑grade AI solutions using AWS Bedrock, Lambda, ECS/EKS and Databricks.
Implement RAG pipelines with Delta tables, Unity Catalog and Databricks Vector Search.
Design and deploy multi‑model agents that dynamically select between LLMs (Claude, GPT, Llama, Titan, etc.) based on task context, cost and latency.
Implement multi‑agent orchestration frameworks enabling collaboration among specialized agents (e.g., data retriever, planner, summarizer, and action executor) for complex construction workflows.
Own full lifecycle delivery – design, development, testing, deployment, monitoring and maintenance.
Full‑Stack & Backend Development
Build APIs, backend services and agentic workflows using Python, FastAPI, LangChain and AWS SDKs.
Create reusable connectors and orchestration layers for multi‑model agents (Claude, GPT, Llama, etc.).
Develop front‑end integrations for Teams and web SPAs via REST or GraphQL endpoints.
Data Engineering & Integration
Partner with Data Engineering to design robust ETL/ELT pipelines from enterprise systems to the Databricks Lakehouse.
Ensure efficient data access, caching and vectorization for low‑latency AI response.
Build tools to monitor and improve data quality, latency and observability.
DevOps & Platform Automation
Use Terraform, AWS CDK and GitHub Actions to automate infrastructure and deployments.
Implement LLMOps: cost monitoring, latency optimization, usage analytics and model versioning.
Enforce security, governance and access standards in line with enterprise policies.
Collaboration & Communication
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
4-6 years of professional software development experience on AWS, with 2+ years focused on AI/ML engineering (LLMs, RAG, Bedrock or similar). Strong coding proficiency in Python (LangChain, FastAPI, boto3) and solid experience with SQL, Databricks and vector databases.
Experience designing and deploying production systems using AWS Lambda, ECS/EKS, API Gateway, Step Functions, S3, CloudFront and KMS.
Strong foundation in CI/CD, IaC (Terraform/CDK) and GitHub Actions.
Experience training, retraining and performing transfer learning on ML models desirable.
Bachelor's in Computer Science, Engineering, Physics or a related field; Master's preferred.
Prior hands‑on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
Excellent collaboration and communication skills – able to work cross‑functionally but not dependent on business‑side facilitation.
Integration & ETL skills: foundational understanding of ETL/ELT design, Airflow or Databricks Workflows and REST/GraphQL API development; proven collaboration with Data Engineering on source‑to‑lake and lake‑to‑agent pipelines.
#LI-JG1
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 stand, 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.
Connect With Us! Not ready to apply? Please submit your resume and/or contact information to Connect with us for general consideration.
#J-18808-Ljbffr
Location:
Boston (US-MA-Boston)
Overview About Suffolk Suffolk is a national enterprise that builds, innovates and invests. It is an end‑to‑end business that provides value throughout the entire project lifecycle by leveraging its core construction management services with vertical service lines that include real‑estate capital investment, design, self‑perform construction services, technology start‑up investment (Suffolk Technologies) and innovation research/development.
Suffolk - America's Contractor - is a national company with more than $5.0 billion in annual revenue, 2,600 employees, and main offices in Boston (headquarters), New York City, Miami, West Palm Beach, Tampa, Estero, Dallas, Los Angeles, San Francisco, and San Diego. It serves clients in every major industry sector, including healthcare, life sciences, education, gaming, transportation/aviation, government, mission‑critical and commercial. Suffolk is privately held, led by founder, chairman and CEO John Fish, and is ranked #8 on ENR's list of "Top CM‑at‑Risk Contractors." Visit www.suffolk.com for more information.
At Suffolk, we believe that our total rewards program should offer you and your family the support you need when it matters most. The program provides employees with access to wide variety of options that can be personalized to support you and your loved ones physically, emotionally, and financially.
Benefits include competitive salaries, auto allowances and gas cards for certain roles, access to market‑leading medical and emotional and mental health benefits, dental and vision insurance plans, virtual care options for physical therapy and primary care, generous paid time off, 401k plan with employer match and access to expert financial resources, company‑paid and voluntary life insurance, tax‑deferred savings accounts, 10 backup daycare days each year, short‑ and long‑term disability, commuter benefits and more.
Role Join Suffolk's AI Studio in Boston as a core engineer transforming how AI powers construction management. Partner with Product Managers, Site AI Engineers and Data Engineers to solve pain points, redesign workflows and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking and more. Focus on building secure, scalable and high‑performance AI agents using modern technologies including AWS Bedrock and Databricks – shaping the backbone of Suffolk's "Construction Site of the Future."
Responsibilities AI Product Engineering & Deployment
Translate product requirements and user stories into production‑grade AI solutions using AWS Bedrock, Lambda, ECS/EKS and Databricks.
Implement RAG pipelines with Delta tables, Unity Catalog and Databricks Vector Search.
Design and deploy multi‑model agents that dynamically select between LLMs (Claude, GPT, Llama, Titan, etc.) based on task context, cost and latency.
Implement multi‑agent orchestration frameworks enabling collaboration among specialized agents (e.g., data retriever, planner, summarizer, and action executor) for complex construction workflows.
Own full lifecycle delivery – design, development, testing, deployment, monitoring and maintenance.
Full‑Stack & Backend Development
Build APIs, backend services and agentic workflows using Python, FastAPI, LangChain and AWS SDKs.
Create reusable connectors and orchestration layers for multi‑model agents (Claude, GPT, Llama, etc.).
Develop front‑end integrations for Teams and web SPAs via REST or GraphQL endpoints.
Data Engineering & Integration
Partner with Data Engineering to design robust ETL/ELT pipelines from enterprise systems to the Databricks Lakehouse.
Ensure efficient data access, caching and vectorization for low‑latency AI response.
Build tools to monitor and improve data quality, latency and observability.
DevOps & Platform Automation
Use Terraform, AWS CDK and GitHub Actions to automate infrastructure and deployments.
Implement LLMOps: cost monitoring, latency optimization, usage analytics and model versioning.
Enforce security, governance and access standards in line with enterprise policies.
Collaboration & Communication
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
4-6 years of professional software development experience on AWS, with 2+ years focused on AI/ML engineering (LLMs, RAG, Bedrock or similar). Strong coding proficiency in Python (LangChain, FastAPI, boto3) and solid experience with SQL, Databricks and vector databases.
Experience designing and deploying production systems using AWS Lambda, ECS/EKS, API Gateway, Step Functions, S3, CloudFront and KMS.
Strong foundation in CI/CD, IaC (Terraform/CDK) and GitHub Actions.
Experience training, retraining and performing transfer learning on ML models desirable.
Bachelor's in Computer Science, Engineering, Physics or a related field; Master's preferred.
Prior hands‑on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
Excellent collaboration and communication skills – able to work cross‑functionally but not dependent on business‑side facilitation.
Integration & ETL skills: foundational understanding of ETL/ELT design, Airflow or Databricks Workflows and REST/GraphQL API development; proven collaboration with Data Engineering on source‑to‑lake and lake‑to‑agent pipelines.
#LI-JG1
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 stand, 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.
Connect With Us! Not ready to apply? Please submit your resume and/or contact information to Connect with us for general consideration.
#J-18808-Ljbffr