Role Overview :

We are seeking a visionary and execution-oriented Chief Technology Officer to lead, scale, and future-proof the technology engine behind Scanalitix.

As CTO, you will own the entire technology roadmap from platform architecture and AI/ML pipelines to Java-based backend systems, DevSecOps, and edge computing infrastructure.

You will build and lead world-class engineering teams, partner closely with the CEO and product leadership, and position Scanalitix as the definitive technology leader in AI-driven surveillance globally.

This is a hands-on leadership role for a builder who thrives at the intersection of deep engineering, product thinking, and strategic business impact.

Key Responsibilities :

1. Technology Vision & Roadmap :

- Define and drive the multi-year technology strategy aligned with Scanalitix's business goals, product vision, and market expansion plans.

- Architect the evolution of the unified platform: VMS, CMS, Video Analytics, and FSM into a cohesive, API-first, modular SaaS offering.

- Stay ahead of AI/ML, edge computing, and video intelligence trends; translating them into defensible product advantages.

- Build the technology brand externally: speaking at conferences, publishing thought leadership, and engaging with analyst communities.

2. Platform & Java Backend Architecture :

- Own the end-to-end platform architecture with Java (Spring Boot / Spring Cloud) as the primary backend foundation.

- Establish architecture standards for microservices, event-driven systems, API gateways, and real-time streaming pipelines.

- Govern technical debt management and enforce engineering quality via code reviews, architecture review boards, and design docs.

- Lead decisions on multi-tenancy, white-labeling, and SaaS-ification of the platform for enterprise and government customers.

- Ensure ONVIF, STQC, and regulatory certifications are maintained and extended across new modules.

3. AI / ML & Video Analytics Leadership :

- Lead the AI/ML engineering function responsible for real-time video analytics: intrusion detection, ANPR, PPE compliance, crowd analysis, loitering, object tracking, and facial recognition.

- Oversee model training, labeling pipelines, model versioning, deployment to edge and cloud (MLOps).

- Drive continuous improvement of detection accuracy, latency, and false-positive reduction.

- Evaluate and integrate third-party AI models and computer vision frameworks where appropriate.

4. Engineering Team Leadership :

- Build, hire, and retain a high-performance engineering organization: backend, frontend, AI/ML, DevOps, QA, and embedded teams.

- Establish a strong engineering culture: ownership, collaboration, continuous learning, and quality-first delivery.

- Implement OKRs, sprint cadences, and engineering KPIs to ensure predictable, high-quality delivery.

- Coach and mentor Engineering Managers, Tech Leads, and Principal Engineers into future leaders.

5. Infrastructure, Cloud & Edge Computing :

- Architect and govern multi-cloud (AWS/Azure/GCP) and on-premise/hybrid infrastructure strategies.

- Oversee edge computing deployments for real-time video processing on constrained hardware (NVR/DVR, smart cameras, edge servers).

- Lead the containerization and orchestration strategy using Kubernetes, Docker, and Helm across production environments.

- Drive infrastructure-as-code practices (Terraform, Ansible) and ensure CI/CD maturity across all engineering teams.

6. Security, Compliance & Certifications :

- Ensure platform-wide security hardening: network segmentation, data encryption, secure APIs, identity management, and SOC 2 readiness.

- Lead compliance for government and defense contracts including STQC, BIS, MeitY guidelines, and CERT-In compliance.

- Establish and oversee vulnerability management, penetration testing, and incident response protocols.

7. Product & Business Partnership :

- Collaborate with the CEO, Product, and Sales teams to translate business requirements into technical deliverables and timelines.

- Represent technology in board meetings, investor presentations, enterprise customer discussions, and government tendering.

- Lead technical due diligence for partnerships, integrations, acquisitions, and funding rounds.

- Define the Make vs. Buy vs. Partner strategy for new capabilities.

Java Tech Stack & Technical Skills Matrix :

1. Java Core Stack :

- Core Language: Java 17/21 (LTS), Core Java, JVM Internals, Concurrency, Memory Management.

- Frameworks: Spring Boot 3.x, Spring Cloud, Spring Security, Spring Batch, Spring Data JPA.

- Microservices: Spring Cloud Gateway, Eureka, Feign, Resilience4j, Circuit Breaker, Config Server.

- ORM & Persistence: Hibernate, JPA, MyBatis, Flyway / Liquibase DB Migrations.

- Build & Dependency: Maven, Gradle, Nexus / JFrog Artifactory.

- Testing: JUnit 5, Mockito, Testcontainers, Spring Boot Test, Cucumber (BDD).

2. Backend & Integration :

- API Design: REST, GraphQL, gRPC, OpenAPI 3.0 / Swagger, API Gateway (Kong, AWS API GW).

- Messaging / Streaming: Apache Kafka, RabbitMQ, MQTT (IoT / Camera feeds), WebSocket, STOMP.

- Databases: PostgreSQL, MySQL, Oracle DB, Redis (Cache), Elasticsearch, InfluxDB (Time-series).

- Search & Analytics: Elasticsearch, OpenSearch, Apache Solr.

- File & Media Storage: MinIO, AWS S3, Azure Blob Storage, HLS / RTSP / ONVIF protocol handling.

3. AI / ML & Video Analytics :

- Computer Vision: OpenCV, DeepStream (NVIDIA), TensorRT, YOLO (v8/v9), RetinaNet, EfficientDet.

- ML Frameworks: TensorFlow, PyTorch, ONNX, Triton Inference Server.

- MLOps: MLflow, Kubeflow, DVC, BentoML, Model Registry, A/B Testing Pipelines.

- Edge AI: NVIDIA Jetson, OpenVINO (Intel), ARM-based inference, TFLite.

- Analytics Use Cases: ANPR, Intrusion Detection, PPE Compliance, Crowd Analysis, Loitering, Facial Recognition, Object Detection.

4. Cloud, DevOps & Infrastructure :

- Cloud Platforms: AWS (EC2, EKS, S3, RDS, Lambda), Azure (AKS, Blob, Azure Media Services), GCP.

- Containerization: Docker, Kubernetes (EKS/AKS/GKE), Helm, Istio, Rancher.

- CI/CD: Jenkins, GitHub Actions, GitLab CI, ArgoCD, SonarQube, Nexus.

- IaC & Automation: Terraform, Ansible, AWS CloudFormation, Packer.

- Observability: Prometheus, Grafana, ELK Stack, Datadog, Jaeger (Distributed Tracing).

- Security: OAuth2 / OIDC / Keycloak, HashiCorp Vault, WAF, SAST/DAST, OWASP ZAP.

5. Surveillance & Domain-Specific :

- Video Protocols: RTSP, ONVIF, HLS, WebRTC, RTMP, MPEG-DASH.

- VMS / NVR Ecosystem: VMS Integration, NVR / DVR Management, PTZ Control, ONVIF Profile S/T/G.

- Field Service Mgmt: Geo-tracking, SLA Engines, Ticketing Integration (ServiceNow / Jira), Mobile SDK.

- Drone Integration: Drone SDK (DJI / ArduPilot), GIS / Mapping APIs, Telemetry Streams.

- Certifications: ONVIF Conformance, STQC Certification, BIS Compliance, MeitY Guidelines.

Required Qualifications :

1. Education :

- B.Tech / M.Tech / M.S. in Computer Science, Electronics & Communications, or related engineering field.

- MBA or equivalent business education is a plus for executive-level stakeholder management.

2. Experience :

- 15-20+ years: total software engineering experience with progressive leadership responsibility.

- 5+ years: in a CTO, VP Engineering, or equivalent executive technology leadership role.

- Java ecosystem: deep hands-on expertise in Java (Spring Boot, Spring Cloud, microservices) at production scale.

- AI/ML products: proven experience shipping real-time AI/ML-powered products to enterprise or government customers.

- Video / surveillance domain: experience with video streaming, analytics pipelines, or edge AI is highly preferred.

- SaaS / Platform: experience building and scaling multi-tenant SaaS platforms serving 100K+ concurrent users.

- Team scale: proven ability to lead and grow engineering organizations of 50-200+ engineers across disciplines.

3. Certifications (Preferred) :

- AWS Certified Solutions Architect - Professional / Google Professional Cloud Architect.

- TOGAF or equivalent Enterprise Architecture certification.

- Certified Kubernetes Administrator (CKA).

- Oracle Certified Java Professional (OCJP / OCP) - a bonus.

- AI/ML certifications (Google ML Engineer, AWS ML Specialty, DeepLearning.AI).

Leadership & Cultural Fit :

- Visionary technologist who can translate complex platform capabilities into business outcomes and investor narratives.

- Hands-on leader who can engage at the architecture whiteboard and the boardroom with equal credibility.

- Empathetic people manager who builds psychological safety, accountability, and a growth mindset in teams.

- Bias for action: comfortable making high-stakes decisions in ambiguous, fast-moving startup environments.

- Strong cross-functional collaborator with Product, Sales, Operations, and Customer Success.

- Track record of on-time delivery of complex platform milestones on a startup budget.

- Passion for AI, surveillance technology, public safety, and building products that matter.