Tech Architect ( Video Analytics )

Tech Architect (Video Analytics)

Engineering / Technology | Hyderabad, India | Full-time | In-office only

About the Role

We are seeking a hands-on Tech Architect to define and drive the technical direction of our SaaS platform. You will architect and build scalable backend web services; design analytics pipelines for drone-captured images and videos; enable enterprise-grade single sign-on (SSO) and a secure, extensible integration layer; and turn proofs of concept (POCs) and prototypes into reliable, production-ready systems. You will also champion AI/LLM-powered agentic coding to improve engineering productivity, while setting high standards for security, quality, scalability, and operational readiness.

Key Responsibilities

· Define end-to-end architecture for a multi-tenant SaaS platform, balancing scalability, performance, security, availability, and cost.

· Assess existing POC and prototype code, determine what can be reused versus re-architected, and define a practical path to production and go-live.

· Production-harden prototypes through robust error handling, logging, monitoring, automated testing, security controls, configuration management, and performance tuning.

· Own production-readiness reviews, load and performance testing, CI/CD and deployment strategies (including blue-green and canary releases), rollback plans, and post-launch support.

· Architect scalable analytics pipelines for drone-captured imagery and video, covering live-stream and bulk-field-upload ingestion, processing, model inference, storage, and API-based delivery of results.

· Address drone-data constraints, including large high-resolution media, intermittent or low-bandwidth connectivity, GPS and flight telemetry, altitude, gimbal/camera orientation, timestamps, and mapping data to missions, sites, and assets.

· Make architecture decisions for real-time versus batch processing, GPU/accelerator utilization, edge versus cloud inference, and cost optimization for media-heavy workloads.

· Architect enterprise identity and SSO using SAML 2.0, OIDC, and OAuth 2.0; support per-tenant SSO configuration, integrations with Okta, Microsoft Entra ID, and Google Workspace, SCIM provisioning, RBAC, and session management.

· Design and own the platform’s extensibility and integration layer, including public APIs, webhooks, SDKs, and plugin/extension models for customer, partner, third-party, drone-platform, and fleet-management integrations, with versioning, backward compatibility, and safe sandboxing.

· Own end-to-end security architecture, including API gateway and WAF controls, authentication and authorization, encryption in transit and at rest, secrets and key management, audit logging, and tenant data isolation.

· Drive secure-by-design practices through threat modelling, security reviews of designs and code, dependency and vulnerability management, and penetration-test remediation—including for AI-generated code and third-party extensions/integrations.

· Architect and oversee backend services, including REST/GraphQL APIs, microservices, and service-to-service communication.

· Remain hands-on: write and review production-grade backend code, build POCs, and demonstrate engineering standards by example.

· Design core SaaS capabilities such as multi-tenancy, subscription and billing integration, tenant data isolation, rate limiting, and horizontal scalability.

· Lead adoption of AI/LLM agentic coding tools such as Claude Code for delivery acceleration, refactoring, and productionizing prototype code.

· Establish workflows and best practices for AI-assisted software development, including code-review standards, guardrails, and quality gates for AI-generated code.

· Define technical standards, coding guidelines, and architectural patterns across engineering teams; evaluate and recommend technologies, frameworks, tools, and emerging AI/LLM and computer-vision capabilities.

· Partner with product managers and stakeholders to translate business requirements into robust technical solutions.

· Review and approve high-level designs (HLDs), guide low-level designs (LLDs), identify technical debt, and lead legacy-system modernization, using AI-assisted tools where beneficial.

· Ensure architecture meets non-functional requirements for scalability, availability, security, tenant isolation, and observability.

· Mentor senior engineers and tech leads on architecture, productionizing prototypes, and effective use of AI coding assistants.

· Lead POCs for new technologies, LLM/agentic workflows, vision models, and major system changes.

· Collaborate with DevOps/SRE teams on infrastructure, deployment, and CI/CD architecture.

· Own architecture documentation and keep it current across the organization.

Required Qualifications & Technical Skills

· 10–15 years of software engineering experience, including significant experience in architecture-focused roles.

· Proven experience building and scaling SaaS products end to end, ideally from early-stage development through growth.

· A demonstrated track record of taking POCs/prototypes to production through refactoring, re-architecture, hardening, and successful live launches with measurable reliability and performance.

· Strong backend engineering experience designing, building, and scaling production REST/GraphQL APIs and microservices.

· Experience designing or building systems that ingest and process drone-generated aerial imagery and video at scale, including use cases such as object detection, change detection, classification, tracking, and inspection.

· Understanding of video streaming protocols (RTSP, RTMP, WebRTC, HLS), encoding/transcoding, and large-scale media storage.

· Experience with drone data and metadata, including geo-tagged imagery, flight telemetry, geospatial context, and data flows from device or ground station to cloud.

· Familiarity with production deployment and serving of computer-vision/ML models, including inference optimization, GPU workloads, batching, and model versioning; exposure to OpenCV, FFmpeg, or similar frameworks.

· Hands-on experience implementing enterprise SSO and authentication using SAML, OIDC, OAuth2, and SCIM in multi-tenant SaaS products, including integration with major identity providers.

· Experience designing extensible platforms with public APIs, webhooks, SDKs, and plugin/extension or third-party integration frameworks, including versioning, rate limiting, and safe extension isolation.

· Strong security architecture skills covering API security, encryption, secrets management, tenant isolation, secure SDLC, threat modelling, and OWASP Top 10 risks and mitigations.

· Mandatory hands-on coding capability; this is an active engineering role, not solely an architecture-review position.

· Practical, demonstrable use of AI/LLM-based agentic coding tools (e.g., Claude Code) in real engineering workflows, beyond casual use.

· Strong expertise in system design, distributed systems, and microservices architecture.

· Experience with multi-tenant architecture, subscription billing systems, and SaaS scalability patterns.

· Hands-on experience with AWS, Azure, or GCP, including managed GPU/ML and media services.

· Deep proficiency in at least one major backend language/stack: Java, Python, Node.js, .NET, or Go.

· Deep understanding of SQL and NoSQL databases, data modelling, caching strategies (Redis or Memcached), and object storage.

· Strong experience with API design, API gateways, messaging/streaming systems such as Kafka or RabbitMQ, and service-integration patterns.

· Experience with CI/CD pipelines, automated testing strategies, and production observability, including logging, metrics, tracing, and alerting.

· Understanding of LLM fundamentals—prompting, context management, tool/function calling, RAG, agentic workflows, and multimodal models—sufficient to architect responsible AI integrations.

· Working knowledge of compliance and data-control frameworks such as SOC 2, ISO 27001, and GDPR, including privacy and data-retention considerations for aerial imagery and video. Regulated-industry experience is a plus, not mandatory.

· Excellent communication skills, including the ability to explain complex technical concepts to non-technical stakeholders.

· Experience leading architecture reviews and building consensus across engineering teams.

Preferred Qualifications

· Experience with drone SDKs/platforms such as DJI, MAVLink, PX4, or ArduPilot, or with drone fleet and mission-management software.

· Experience with geospatial and photogrammetry tooling, including GIS, orthomosaics, 3D reconstruction, GDAL, or PostGIS.

· Experience with edge/on-device inference or low-latency real-time video processing at a ground station or on a drone.

· Experience with video analytics platforms or stream-processing frameworks such as GStreamer, NVIDIA DeepStream, or Triton Inference Server.

· Experience building a developer ecosystem or marketplace, including partner APIs, app/extension marketplaces, and developer portals.

· Experience with zero-trust architecture, mutual TLS (mTLS), WAF/API-gateway policy design, or security tooling such as SAST/DAST and SIEM integrations.

· Experience with API monetization, usage-based billing, or SaaS metering systems.

· Experience building or integrating LLM-powered applications or agents in production.

· Familiarity with MCP (Model Context Protocol) or similar agent-tooling frameworks.

· Experience with Docker, Kubernetes, or other containerization and orchestration technologies.

· Familiarity with Infrastructure as Code (IaC), including Terraform or CloudFormation.

· Experience with SRE practices, including SLOs/SLAs, incident response, and capacity planning.

· Prior experience scaling SaaS systems from startup to enterprise scale.

· Relevant certifications, such as AWS/Azure/GCP Solutions Architect, TOGAF, or security certifications.

Role Expectations

· Be a hands-on technical leader who can move fluidly between architecture, implementation, code review, production readiness, and technical mentoring.

· Balance rapid delivery with long-term maintainability, security, reliability, and cost efficiency.

· Build consensus across teams and communicate trade-offs clearly to both technical and non-technical stakeholders.

Application note: Candidates should be prepared to demonstrate hands-on backend engineering, productionizing POCs, SaaS architecture, drone-media/data pipeline design, enterprise SSO and security architecture, and practical use of AI-assisted coding tools.

Pay: ₹2,500,000.00 - ₹3,000,000.00 per year

Work Location: In person