
201 - 500 employees
Founded 2002
💼 Consulting
📦 Logistics
🏭 Manufacturing
💰 Private equity on 2024-03
Consulting • Logistics • Manufacturing
Bits In Glass is a global boutique consulting firm that designs, builds, and manages intelligent automation and integration solutions for enterprise clients. The company specializes in enterprise AI and data engineering, low-code/no-code development, process automation (including RPA and BPA), enterprise application integration, CRM implementations, and application management services, working with partners like Appian, AWS, UiPath, MuleSoft, Snowflake, and Creatio. Bits In Glass serves industries such as banking and financial services, insurance, transportation and logistics, manufacturing and distribution, real estate, healthcare, and the public sector, helping organizations scale automation, improve efficiency, and turn data into actionable insights.
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201 - 500 employees
Founded 2002
💼 Consulting
📦 Logistics
🏭 Manufacturing
💰 Private equity on 2024-03
Consulting • Logistics • Manufacturing
Bits In Glass is a global boutique consulting firm that designs, builds, and manages intelligent automation and integration solutions for enterprise clients. The company specializes in enterprise AI and data engineering, low-code/no-code development, process automation (including RPA and BPA), enterprise application integration, CRM implementations, and application management services, working with partners like Appian, AWS, UiPath, MuleSoft, Snowflake, and Creatio. Bits In Glass serves industries such as banking and financial services, insurance, transportation and logistics, manufacturing and distribution, real estate, healthcare, and the public sector, helping organizations scale automation, improve efficiency, and turn data into actionable insights.
• Shape client engagements during the sales cycle by assessing technical feasibility and realistic 8–12-week production scope • Push back on requirements that cannot be delivered before contractual commitments • Own architecture decisions covering model selection, build versus buy, accelerator reuse, bespoke work, and hosting approach • Write technical sections of proposals and statements of work • Help define measurable and defensible outcome metrics • Represent ConveneAI in client architecture, security, and vendor review boards • Run architecture reviews at kickoff and defined gates for every live engagement • Govern decisions involving data residency, inference hosting, identity and access, network isolation, and systems-of-record integration • Unblock pods through pairing and review • Own technical escalations and provide candid status assessments to the Product Owner and leadership • Monitor inference cost, latency, and reliability across engagements • Own the ConveneAI reference architecture and accelerator library • Set standards for agent design, evaluation, observability, security, and cost management • Evaluate models, frameworks, and tooling for inclusion in the standard stack • Build reusable technical assets that improve pod delivery efficiency • Mentor GenAI Engineers and Data Engineers through design and code review • Interview and calibrate technical hires and help define the engineering career path • Collaborate with senior AI architects across the global operating bench to maintain consistent standards • Read code, prototype solutions, and defend designs before bank and insurer architecture review boards
• 10 or more years building and shipping enterprise software • At least 2 years on production LLM or agentic systems that real users depended on • Track record as the technical owner across multiple concurrent client engagements • Deep hands-on capability with Python, cloud architecture (AWS, Azure, or GCP), distributed systems, and API and integration design • Production experience with agent architectures, retrieval at enterprise scale, evaluation, cost per task, latency, observability, and AI-system failure modes • Enterprise architecture fluency covering identity and access, security posture, data residency, network isolation, and model hosting options • Experience getting a regulated client's review board to approve a design • Commercial literacy, including understanding how architecture decisions affect gross margin on fixed-fee engagements • Credibility with client CIOs or Chief Architects and hands-on engineers • Judgement to recommend against undeliverable deals and hold that position under commercial pressure • Legally entitled to work in Canada • Willing to travel to client sites • Bonus: architecture leadership at a consultancy or systems integrator, or Field CTO/principal architect experience at an AI, data, or cloud platform vendor • Bonus: regulated-industry experience with systems such as Guidewire, Duck Creek, core banking, or clinical systems • Bonus: self-hosted or open-weight model deployment, fine-tuning, distillation, and private inference architecture • Bonus: experience building reusable reference architectures or accelerator libraries • Bonus: experience scaling a delivery organisation • Bonus: published writing, conference talks, or open-source work on applied AI architecture
• Meaningful equity at the stage where technical decisions determine whether the delivery model scales or stalls • Initial employment on Bits In Glass payroll with intended transition to a permanent position directly with Convene AI after approximately 12–18 months, subject to business requirements and transition arrangements • Collaboration with the support, culture, and established consulting expertise of Bits In Glass • Direct working relationship with the founders and senior AI operators • Genuine breadth across pre-sales shaping through production operations and multiple industries
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