Suffolk is looking to transform how AI powers construction management by solving pain points, redesigning workflows, and deploying AI agents to improve efficiency in reporting, RFIs, planning, progress updates, and materials tracking.
Requirements
- 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.
- 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.
Responsibilities
- 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 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.
- 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.).
- Use Terraform, AWS CDK, and GitHub Actions to automate infrastructure and deployments.
Other
- Partnering with Product Managers, Site AI Engineers and Data Engineers
- 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.
- Bachelors in Computer Science, Engineering, Physics, or a related field; Masters preferred.
- Prior hands-on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
