AI Engineer 100% Remote

AI Engineer 100% Remote Responsibilities: • Opportunity hunting and workflow redesign Lead Lean/Six Sigma discovery workshops; map value streams, assess process and data maturity, and log low-effort/high-impact AI use cases. • Process and data maturity assessment Evaluate each jobsite's current workflows and underlying data; surface gaps that block AI adoption and develop phased improvement plans with Operations Excellence to establish the right process baseline before deploying agents. • Assess the market solutions Evaluate off-the-shelf and platform tools; launch pilots, measure impact, and scale wins. • Rapid AI-agent builds Convert user stories into production-ready agents in Copilot Studio / Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks within days; wire them to Teams/SharePoint on the front end and Databricks Lakehouse or other sources on the back end. • Enterprise-grade engineering & LLMOps Build RAG pipelines backed by Delta tables, Unity Catalog, and Databricks Vector Search; automate infra with GitHub Actions / Posit; monitor latency, cost, adoption, and drift. • Data integrations Partner with Data Engineering to design and maintain ETL pipelines, API integrations, and event-driven connectors feeding RAG and agents. • Cross-cloud orchestration Blend OpenAI, Azure OpenAI, and AWS Bedrock behind secure custom connectors; package agents for seamless rollout. • Change enablement Train crews, gather feedback, iterate, and track adoption and ROI metrics; apply influence model principles to embed agents into daily routines and SOPs, and track behavior change KPIs. • Stakeholder communication Brief project leadership and clients on agent impact in clear business terms; contribute use cases and playbooks for Suffolk's "Construction Site of the Future." • Escalation & hand-off Draft clear user stories, data specs, and acceptance criteria for any complex solution that requires the central AI Solution Engineers or Data Engineering / Data Science team to lean in. • Compliance Ensure every on-site AI tool meets Suffolk's information security, data governance, and client confidentiality standards. Qualifications: • 4 6+ years in AI engineering / full-stack data applications or data science, including 2+ years building production LLM/RAG solutions. • Bachelor's in CS, 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. • Demonstrated process excellence background (Lean/Six Sigma Green Belt or equivalent) with experience diagnosing process and data gaps and supporting change management plans with Operations Excellence. • Strong facilitation and communication skills. • Hands-on expertise with Copilot Studio, Power Apps/Automate, custom connectors, and CoE Toolkit governance. • Programming & data stack: Python, SQL, Databricks Lakehouse, vector stores. • DevOps & IaC: GitHub Actions (or Azure DevOps) and Posit Workbench/Connect automation or comparable CI/CD tooling; strong Git/GitHub workflow discipline. • 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. • Willing and able to travel and work on active jobsites. Apply tot his job Apply To this Job