Aegistech Jobs in Usa

2 positions found

AI Engineer
🏒 Aegistech
Salary not disclosed
New Haven, CT 5 days ago

Role:

Join project teams across the U.S. as the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the β€œConstruction Site of the Future,” showing how agentic AI will transform project operations.


Location: New Haven, Connecticut


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 β€œConstruction 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.


Qualifications:

  • 3+ 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.
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Technical Product Manager, Functional AI
🏒 Aegistech
Salary not disclosed
Boston, MA 5 days ago

Role:

The Technical Product Manager, Functional AI, will lead the definition and delivery of AI solutions that transform our core business functions, including Finance, HR, Legal, Marketing, and others. This role bridges functional expertise and technical executionβ€”partnering with business leaders to identify opportunities, shaping requirements into scalable AI solutions, and ensuring adoption that delivers measurable value. The Technical Product Manager will collaborate closely with engineers and data teams to design, pilot, and scale solutions, while maintaining clear visibility into ROI and impact for leadership. Success in this role requires strong product management discipline, applied AI expertise, and the ability to translate complex technical concepts into business outcomes.


Responsibilities:


Product Management & Business Partnership:

  • Lead discovery and scoping sessions with business stakeholders across corporate functions (Finance, HR, Marketing, etc.) to identify high-value AI opportunities.
  • Build strong relationships with functional leaders to understand workflows, pain points, and success measures.
  • Translate business requirements into clear technical requirements that guide design, engineering, and vendor evaluation.
  • Drive user experience design by ensuring solutions are intuitive, accessible, and aligned with employee needs.
  • Prepare clear documentation of requirements, workflows, and decision rationale to support transparent delivery.
  • Lead Agile sprint planning, backlog grooming, and retrospectives to ensure timely and high-quality delivery of product features in collaboration with cross-functional teams.


AI Solution Design & Delivery Support:

  • Partner with engineers to shape solution approaches, balancing build/buy/partner considerations.
  • Contribute to solution architecture discussions, ensuring designs are scalable, secure, and compliant with standards.
  • Collaborate closely with delivery teams to validate functionality against requirements, proactively evaluate feature effectiveness and accuracy, and resolve scope or design ambiguities to ensure product quality and alignment with user needs.
  • Support testing, pilot deployment, and adoption efforts, incorporating user feedback into iterative improvements.
  • Document and communicate lessons learned, value metrics, and impact stories to demonstrate business outcomes.


Value & Impact Measurement:

  • Define success metrics and measurable outcomes for each AI initiative in partnership with business stakeholders.
  • Work closely with the Data Analytics team to design and maintain value tracking reports and dashboards.
  • Monitor adoption, efficiency gains, and ROI, and proactively identify areas for improvement.
  • Present value realization updates to leadership, ensuring clear visibility into the business impact of AI solutions.


Qualifications:

  • At least 5 years of experience in technical product management with a minimum of 2 years in AI-related products.
  • Bachelor’s and Master’s in Computer Science, Physics, Engineering, or associated quantitative fields.
  • Have proven experience and knowledge of corporate functions (Finance, HR, Legal, Marketing, etc.)
  • Exceptional facilitation and communication skillsβ€”comfortable running discovery sessions, white-boarding with PMs, and demoing prototypes to senior leaders.
  • Demonstrated product-management mindset: roadmap ownership, KPI definition, and budget/risk trade-off communication.
  • Hands-on experience leading change initiatives and measuring adoption by teams.
  • Strong analytical and problem-solving skills
  • Excellent communication and collaboration skills
  • Ability to articulate technical concepts to non-technical stakeholders
  • Deep understanding of AI applications, tools, and methodologies
  • Proven ability to apply AI/ML techniques (e.g., NLP, document intelligence, predictive modeling, generative AI) to solve business problems in corporate functions.
  • Hands-on experience with modern AI/ML tools and platforms (e.g., OpenAI, Azure AI, AWS SageMaker, AWS Bedrock or similar).
  • Familiarity with the latest trends in AI (e.g., agentic AI, multimodal models, RAG) and ability to evaluate their relevance for client use cases.
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