Role Description We are seeking an experienced Industrial IoT (IIoT) Engineer to design and build connected, data-driven industrial systems spanning the factory floor to enterprise cloud platforms. In this role you will architect end-to-end IIoT solutions, including: - Edge data acquisition - Secure connectivity - Cloud ingestion - Real-time analytics - Operational dashboards The ideal candidate will combine strong software engineering skills with practical experience in industrial protocols, edge computing, and cloud IoT platforms. You will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions. You will also be expected to raise the bar through code review, design review, and mentorship of more junior engineers. Key Responsibilities - Architect end-to-end IIoT solutions spanning edge devices, gateways, connectivity, and cloud platforms. - Design data acquisition pipelines from PLCs, SCADA, and sensors using protocols such as OPC UA, Modbus, MQTT, and Sparkplug B. - Build edge computing applications using AWS IoT Greengrass, Azure IoT Edge, or similar platforms. - Implement secure connectivity using mTLS, certificate management, and zero-trust patterns. - Build cloud ingestion and processing pipelines using AWS IoT Core, Azure IoT Hub, Kafka, or similar. - Develop real-time analytics, anomaly detection, and predictive maintenance models that turn raw telemetry from industrial assets into actionable signals for operators and reliability engineers. - Build operational dashboards and alerts for plant managers and operators. - Integrate IIoT data streams with MES, ERP, CMMS, and historian systems, designing reliable bidirectional flows that maintain consistency between operational technology and enterprise systems of record. - Implement strong device management, including provisioning, OTA updates, and certificate rotation. - Collaborate closely with OT, process engineering, and reliability teams, gathering requirements, aligning on technical approach, and ensuring that delivered solutions meet both functional needs and broader engineering and operational standards. - Ensure compliance with relevant industrial cybersecurity standards (IEC 62443, NIST). - Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures. - Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing. - Continuously evaluate emerging IIoT technologies and platforms, assessing maturity, fit for purpose, and total cost of ownership. Qualifications - Bachelor’s degree in Computer Science, Engineering, or a related technical discipline. - Five or more years of IIoT or industrial software engineering experience. - Strong programming skills in Python, C++, or Go. - Hands-on experience with industrial protocols (OPC UA, Modbus, MQTT, Sparkplug B). - Experience with at least one major cloud IoT platform (AWS, Azure, GCP). - Hands-on experience with edge runtimes (Greengrass, IoT Edge). - Solid understanding of OT/IT integration patterns. - Experience with streaming and real-time analytics platforms. - Familiarity with industrial cybersecurity standards. - Excellent troubleshooting, communication, and documentation skills. Preferred Qualifications - Experience with digital-twin platforms. - Hands-on experience with predictive maintenance ML models. - Exposure to time-series databases (InfluxDB, TimescaleDB). - Familiarity with Unified Namespace (UNS) patterns. - Industrial certifications (ISA, IEC 62443). How to Apply For immediate consideration, please send your resume to [email protected] . Learn more about Bright Vision Technologies at www.bvteck.com .

Role Description We are looking for a Product Support professional to join our Product Support team at EquiLend. As part of our global Product Support team, you will play a vital role in ensuring the smooth operation of the systems that power the global securities finance ecosystem. Operating in a high-availability production environment, this position demands both deep technical expertise and strong analytical ability. You will lead the response to complex incidents, conduct root-cause analyses, and help drive automation and stability across our systems. Working closely with our engineering, DevOps, and infrastructure teams, you’ll help strengthen operational resilience and deliver a best-in-class client experience. We currently have opening for permanent night shift. Below are the details: - Night Shift: 5 days per week, 9:00 pm - 6:00 am IST - Work model: Remote What You’ll Do - Manage and resolve complex production issues across our global product suite, ensuring timely diagnosis and resolution. - Conduct in-depth root-cause analysis across distributed systems, databases, and microservices architectures. - Develop and optimise SQL scripts and Python-based utilities to enhance operational monitoring and automation. - Monitor production environments, identify anomalies, and take proactive corrective action. - Collaborate with DevOps and infrastructure teams to enhance observability, automation, and system reliability. - Contribute to release validation, post-deployment testing, and system health checks. - Create and maintain detailed operational documentation, including runbooks and troubleshooting guides. - Provide mentorship and escalation support to junior members of the team. - Identify recurring issues and propose automation or process improvements to prevent reoccurrence. - Ensure adherence to operational risk controls, audit requirements, and internal service standards. Qualifications - 5+ years of relevant commercial experience in a product, application, or production support role. - Experience supporting external clients, ideally within SaaS, enterprise platforms, or technology-driven environments. - A solid understanding of Linux/Unix operating systems, including basic command-line usage and log analysis. - Working knowledge of SQL to support client investigations and basic data analysis. - Excellent written and verbal communication skills in English, with the ability to clearly explain technical issues to clients and internal teams. - Strong collaboration skills and a willingness to work closely with senior support engineers and cross-functional teams. - Ability to prioritise tasks effectively in a fast-paced, production support environment. - A client-focused mindset with a proactive and structured approach to problem-solving. - Exposure to Financial Services or Capital Markets environments is highly desirable but not essential. Benefits - Be rewarded for your impact through an annual performance-linked variable pay award, in addition to your fixed CTC. - Work flexibly with up to 100 remote working days per year. - Take time to recharge with 32 days of paid leave per year, comprising paid, casual, and sick leave, plus public holidays. - Access comprehensive health insurance for you and your dependents from your first day. - Receive personal accident insurance from the start of your employment. - Connect with colleagues at an annual company-sponsored team retreat, hosted at a new location each year. - If relocating from more than 40 miles away, receive hotel accommodation and travel ticket reimbursement. Company Description EquiLend is a global financial technology firm at the center of the securities finance industry. Since 2001, we have built the infrastructure that financial institutions rely on to trade, manage, and report. This includes products such as our NGT trading platform, Post Trade Suite, DataLend market intelligence, RegTech solutions, and EquiLend Clearing Services. We operate across North America, EMEA, and Asia-Pacific, working with banks, broker dealers, asset managers, and custodians to bring greater efficiency, transparency, and automation to the securities finance lifecycle. Our teams combine deep market expertise with a focus on building technology that works at scale, under real-world conditions, for some of the world's most demanding financial institutions. EquiLend is Great Place to Work Certified™ in the U.S., UK, Ireland, and India, and has been recognized as Global Data Provider of the Year and Regulatory Solution of the Year at the Securities Finance Times Industry Excellence Awards 2025.

Role Description We are seeking a Forward Deployed Engineer (FDE) with deep expertise in Google Cloud and applied AI to embed directly with our enterprise customers and turn frontier AI capabilities into production-grade systems. This role is for an engineer who thrives on ambiguity, codes alongside customer teams, and owns AI initiatives end-to-end — from technical discovery through architecture, build, deployment, and handoff. The ideal candidate has shipped agentic AI solutions on Google Cloud, is fluent in Vertex AI and Gemini, and is comfortable architecting multi-agent systems, RAG pipelines, and tool-calling integrations against messy enterprise environments. You will operate as an embedded builder — not an advisor — writing production code, debugging live systems, and co-developing with the customer’s engineering team to instill Google-grade engineering best practices and accelerate AI adoption. This position is remote and may require occasional travel. Role Responsibilities - Embed within customer engineering teams and lead technical discovery sessions with business stakeholders, engineering leadership, and security to translate ambiguous business problems into clear AI architectures and delivery plans. - Architect, code, and ship production-grade agentic AI solutions on Google Cloud — including multi-agent systems, MCP servers, sub-agents, skills, connectors, agentic wrappers, and safety guardrails — that move customers beyond pilots into measurable business value. - Design and implement Retrieval-Augmented Generation (RAG) pipelines and grounding architectures, including chunking strategy, vector databases, and embedding optimization to prevent hallucinations and ensure response quality. - Build the “connective tissue” between Google’s AI products and customer infrastructure, including APIs, legacy data silos, identity, and security perimeters. - Implement multi-agent patterns such as ReAct, self-reflection, and hierarchical delegation using frameworks like Google’s Agent Development Kit (ADK) or LangGraph. - Build high-performance evaluation pipelines and observability frameworks for agentic systems, with attention to accuracy, safety, latency, cost-per-request, and tokens-per-second. - Debug agent logic and optimize tool selection in live, high-traffic environments, including tracing conversation and request IDs across microservices to resolve production failures. - Co-build with customer engineering teams and act as a hands-on advocate for AI-assisted development, introducing and operationalizing AI coding tools to accelerate delivery and elevate engineering practices. - Drive a deliberate handoff to the customer’s team, ensuring long-term ownership, documentation, and end-user adoption after the engagement concludes. - Develop and maintain technical documentation, architecture decision records, and evaluation results across all assigned engagements. Qualifications - Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience. - 5+ years of software development experience using Python, TypeScript, or comparable languages, with a track record of shipping production-grade code to external or internal customers. - Hands-on experience architecting and deploying AI systems on Google Cloud Platform (GCP), including: - Vertex AI — model deployment, fine-tuning workflows, evaluation, and platform-level observability. - Gemini models — prompt engineering, structured outputs, function/tool calling, and multimodal use cases. - BigQuery and Cloud Storage — as data and grounding sources for AI workloads. - Cloud Run, Cloud Functions, and Pub/Sub — for deploying and orchestrating agentic services. - Gemini Enterprise Agent Platform — designing, configuring, and deploying enterprise-grade agents, grounding on customer data sources, integrating tools and connectors. - Demonstrated experience building agentic and AI-driven solutions in production, including: - LLM application development — prompt engineering, agent development, and evaluation frameworks. - RAG architectures — vector databases, chunking strategy, and retrieval evaluation. - Data pipelines — structured and unstructured data ingestion to power enterprise-grade AI solutions. - Experience deploying cloud resources via Terraform or similar infrastructure-as-code tools. - Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI requirements and translate ambiguous business goals into technical roadmaps. - Experience integrating AI systems with enterprise IT infrastructure, including authenticated APIs, legacy data systems, and corporate security perimeters. - Ability to travel up to 50% of the time to customer sites. - Outstanding communication skills, including the ability to explain complex AI and architectural concepts to both deep-technical engineers and non-technical executives. Nice to Have Qualifications - Master’s degree or PhD in AI, Computer Science, Machine Learning, or a related technical field. - Experience implementing multi-agent systems using frameworks such as Google’s Agent Development Kit (ADK), LangGraph, or CrewAI, and complex agent patterns including ReAct, self-reflection, and hierarchical delegation. - Hands-on experience designing and deploying Model Context Protocol (MCP) servers, tool-calling protocols, and connector ecosystems for agentic systems. - Knowledge of “LLM-native” operational metrics (tokens/sec, cost-per-request, time-to-first-token) and techniques for optimizing state management, granular tracing, and conversation-ID propagation across microservices. - Track record of troubleshooting live, high-traffic production AI systems during critical windows. - Experience architecting AI solutions within complex infrastructures, including data sovereignty, secure governance, and air-gapped or regulated environments. - Experience designing user-facing interfaces for AI and agentic systems with attention to context engineering, transparency, and explainability. - Experience driving organization-wide initiatives (e.g., migrations to new AI stacks, engineering-velocity programs) that deliver measurable improvements to engineering productivity and business outcomes. - Experience as an advocate for AI-assisted software development, including introducing AI coding assistants to enterprise engineering teams and developing internal best practices for their use. - Google Cloud certifications: - Google Cloud Professional Machine Learning Engineer - Google Cloud Professional Cloud Architect - Google Cloud Professional Data Engineer - Familiarity with full-stack application development and REST/GraphQL API design. Benefits - This is a full-time position based in Quebec, Canada. - Valtech offers a comprehensive benefits package effective after three months of continuous service: - A comprehensive insurance plan, where you can choose the module that best suits your needs—Gold, Silver, or Bronze. The employer may contribute up to 80% of your coverage depending on the selected module. This plan includes short- and long-term disability coverage. - Dialogue via Sun Life provides virtual healthcare services, allowing you to consult with a healthcare professional for emergencies, prescription renewals, and more. You also have access to the Employee and Family Assistance Program, as well as a complete mental health support program. - A $500 Personal Spending Account, which can be used for healthcare reimbursements, gym memberships, public transit passes, office supplies, or contributions to your RRSP through Valtech. - A retirement plan where Valtech will match 100% of your RRSP contributions through a Deferred Profit Sharing Plan (DPSP), up to a maximum of 4%. You can start contributing to your RRSP immediately, and to the DPSP after 3 months. The vesting of the DPSP will be after 24 months of service. - Access to flexible vacation under Valtech's policy to support your work-life balance, with 5 days available during your probation period and a prorated amount calculated for the remainder of the year. - Personal Technology Reimbursement – $30/month for every employee-offered on day 1. - We close during the winter holidays and offer flexible scheduling throughout the year, so you can enjoy those sunny Friday afternoons—provided your weekly hours are completed. Your Application Process Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential. ⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses. We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.

• Technology: Cisco Meraki & Fortinet - SD-WAN, SD-LAN & Wi-Fi - if possible, SASE Services as well for each Technology • Development of HLD/LLD to win Customer Project • Development and Testing of the Services at each of the Platform and Services • Post sales Support Function to help Customer Success • Platform Owner Function, Capacity Management • Test LAB Support and Sales Trainings • All Over Engineering Tasks Underlay & Overlay Network • Lead the migration from traditional MPLS networks to hybrid SD-WAN architectures • Fill out ECDC (End customer data collection form) for complex customer solutions • Attend technical SD WAN rollouts (remotely)