
1001 - 5000 employees
đ° $82.2M Venture Round on 2022-12
As a global engineering firm, we design infrastructure solutions that connect and elevate communities. That means enhancing conventional designs with smarter, more resilient systems. Connecting gridlocked populations with better means of mobility. Stewarding precious resources with more sustainable solutions. And solving our clientâs unique challenges with innovative and technically advanced approaches.
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1001 - 5000 employees
đ° $82.2M Venture Round on 2022-12
As a global engineering firm, we design infrastructure solutions that connect and elevate communities. That means enhancing conventional designs with smarter, more resilient systems. Connecting gridlocked populations with better means of mobility. Stewarding precious resources with more sustainable solutions. And solving our clientâs unique challenges with innovative and technically advanced approaches.
⢠Design and architect AI-driven applications and enterprise integrations ⢠Lead development of retrieval-augmented generation and LLM-based workflows ⢠Define engineering standards, code quality practices, and review processes ⢠Support monitoring, evaluation, and continuous optimization of deployed models ⢠Operate in a fast-evolving environment with ambiguous requirements ⢠Balance speed of delivery with long-term architectural soundness ⢠Partner closely with the AI Delivery Manager to align technical execution with business priorities ⢠Own and guide technical and architectural decisions across AI systems, cloud infrastructure, and enterprise integrations ⢠Drive hands-on development and ensure delivery of production-ready AI systems
⢠Required experience delivering AI/ML or data products into production environments ⢠Strong understanding of system architecture (APIs, data pipelines, cloud platforms) ⢠Proven ability to lead technical direction and mentor engineers ⢠Experience building solutions aligned to measurable business outcomes ⢠Preferred experience with Azure AI services, Microsoft AI Foundry (Azure AI Studio), vector databases, or LLM-based systems ⢠Familiarity with MLOps practices ⢠Experience in consulting or enterprise environments
⢠extensive medical insurance coverage ⢠disability insurance ⢠life insurance ⢠continuing education benefits ⢠paid time off ⢠employee assistance program ⢠retirement savings plan with company matching contributions
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