Manager - Configuration Engineering AI - Pune - WeAgile Software Solutions Pvt. Ltd.

    WeAgile Software Solutions Pvt. Ltd.
    WeAgile Software Solutions Pvt. Ltd. Pune

    4 days ago

    Technology / Internet
    Description

    About WeAgile Software Solution Pvt. Ltd:

    We are a leading technology firm that integrates strategy, design, and software engineering to enable enterprises and technology disruptors across the globe to thrive as modern digital businesses. Ongoing digital disruption is challenging enterprises to keep pace with the accelerating rate of technological change. This is where WeAgile can help. We leverage our vast experience to improve our clients' ability to respond to change; utilize data assets to unlock new sources of value; create adaptable technology platforms that move with business strategies; and rapidly design, deliver, and evolve exceptional digital products and experiences at scale.

    About the Role

    The Manager - Configuration Engineering AI owns the technical implementation and onboarding of our computer vision analytics platform across multi-site customer environments. This is a hands-on role responsible for designing, configuring, validating, and optimizing camera-based analytics deployments.

    You will bridge pre-sales and post-sales execution—translating customer use cases into concrete technical configurations and ensuring cameras, data pipelines, and analytics are correctly deployed. Success in this role means customers achieve accurate insights quickly, including foot traffic, queue times, product interactions, and loss-prevention metrics.

    Core Responsibilities

    Technical Deployment & Configuration

    • Lead hands-on onboarding from kickoff through go-live across multiple customer locations.
    • Define and validate camera placement, field of view, and store layout considerations impacting analytics accuracy.
    • Configure and validate analytics, including lines, polygons, zones, gates, and mappings for each camera.
    • Perform calibration and accuracy validation for people counting, vehicle detection, and traffic flow analytics.
    • Support camera feed ingestion, connectivity, and data flow from edge to platform.

    Troubleshooting & Quality Assurance

    • Translate customer business use cases into technical system configurations.
    • Escalation points for configuration related issues from Support team.
    • Diagnosing and resolving issues related to video streams, inference accuracy, latency, and data gaps.
    • Coordinate Quality Assurance activities to continuously evaluate data accuracy and provide reports to customers and internal stakeholders.

    Multi-Site Project Execution

    • Manage technical onboarding for multi-site retail deployments with clear timelines and deliverables.
    • Maintain store-level configuration documentation, rollout templates, and technical SOPs.
    • Provide regular technical status updates to internal teams and customer stakeholders.

    Cross-Functional Collaboration

    • Partner with Sales and Solutions Engineering to ensure accurate technical scoping and onboarding readiness.
    • Collaborate with Product to provide structured feedback on model performance, accuracy, and usability.
    • Coordinate with implementation partners, vendors, and customer IT teams during deployment.

    Metrics & Continuous Improvement

    • Monitor data accuracy and maintain feedback loops to Product and Engineering
    • Track onboarding KPIs such as time-to-first-insight, model accuracy, and onboarding quality.
    • Identify gaps and recommend improvements to onboarding tools, processes, and scalability.

    What This Role Is

    • Hands-on configuration, calibration, and validation of computer vision systems
    • Technical owner of customer onboarding success
    • A bridge between customer environments and internal engineering teams

    What This Role Is Not

    • A purely project-management or customer success coordination role
    • A support-only or documentation-only function

    Skills & Qualifications

    • Overall 7+ years of experience and2+ years in QA and/or labeling within ML Ops type of environment
    • 2+ years managing a team of 5 or more
    • Familiarity with computer vision concepts and methods to evaluate accuracy
    • Experience with configuration, calibration, and validation of computer vision systems
    • Proven ability to design, document and improve processes
    • Track record of leveraging critical thinking to deliver complex solutions
    • Excellent communication and stakeholder management skills
    • BONUS: Understanding of retail operations and KPIs such as traffic conversion, merchandising compliance, and loss prevention.
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