AI Engineer

AI Engineer in Suffolk Construction Company, Inc.'s AI Studio in Boston, onsite, building scalable AI agents and platforms to power construction management, collaborating with Product Managers, Site AI Engineers, and Data Engineers.

Responsibilities

• Translate product goals and user stories into production AI solutions using AWS Bedrock, Lambda, ECS/EKS, and Databricks.
• Build retrieval augmented generation pipelines leveraging Delta tables, Unity Catalog, and Vector Search.
• Architect and deploy multi-model agents that automatically select among LLMs such as Claude, GPT, Llama, Titan, based on task context, cost, and latency.
• Design multi-agent orchestration frameworks enabling collaboration among specialized agents (data retriever, planner, summarizer, action executor) for complex construction workflows.
• Own end-to-end delivery lifecycle — design, development, testing, deployment, monitoring, and maintenance.
• Develop APIs, backend services, and agent workflows using Python, FastAPI, LangChain, and AWS SDKs.
• Create reusable connectors and orchestration layers for multi-model agents (Claude, GPT, Llama, etc.).
• Implement front-end integrations for Teams and web SPAs via REST or GraphQL endpoints.
• Collaborate with Data Engineering to design robust ETL/ELT pipelines from enterprise systems to the Databricks Lakehouse.
• Ensure efficient data access, caching, and vectorization to support low-latency AI responses.
• Build tools to monitor data quality, latency, and observability.
• Utilize Terraform, AWS CDK, and GitHub Actions to automate infrastructure and deployments.
• Implement LLMOps including cost monitoring, latency optimization, usage analytics, and model versioning.
• Enforce security, governance, and access controls in line with enterprise policies.
• Collaborate closely with product managers, site AI engineers, and data scientists to iterate rapidly in Agile sprints.
• Communicate technical progress to non-technical stakeholders and contribute to internal AI playbooks and templates.

Requirements

• 4-6 years of professional software development on AWS, with at least 2 years in AI/ML engineering (LLMs, RAG, Bedrock, or equivalent). Proficient in Python (LangChain, FastAPI, boto3) and solid SQL, Databricks, and vector database experience.
• 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 is desirable.
• Bachelor’s degree in Computer Science, Engineering, Physics, or related field; Master’s preferred.
• Hands-on experience in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
• Excellent collaboration and communication skills, able to work cross-functionally with minimal business-side facilitation.
• Foundational integration and ETL skills: 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.

Compensation

Base salary: USD 107,000 - 222,600 per year.

Benefits

• Competitive base salaries
• Auto allowances and gas cards for certain roles
• Market-leading medical, emotional, and mental health benefits
• Dental insurance
• Vision insurance
• Virtual care options for physical therapy and primary care
• Generous paid time off
• 401(k) plan with employer match and access to financial resources
• Company-paid and voluntary life insurance
• Tax-deferred savings accounts
• Ten backup daycare days each year
• Short- and long-term disability
• Commuter benefits