We are seeking a Lead Engineer with a strong background in software engineering, security architecture, and system design to lead the technical direction of our enterprise applications. You will work at the intersection of development and security, driving "Security by Design," establishing NFRs (performance, scalability, reliability), and crafting high-level solution architectures. You will mentor developers, influence technical stakeholders, and ensure that software is secure, resilient, and performant. This role involves hands-on architecture, security governance, and implementing scalable, secure-by-design AI workloads.

Required Skills & Qualifications

• Experience: 10-15 years in software engineering, with at least 3-5 years in a lead or security architect role.
• Security Expertise: Strong understanding of OWASP top 10, Dev Sec Ops, IAM, encryption, and data protection controls.
• Cloud Proficiency: Hands-on experience with Azure, or GCP cloud-native architectures.
• Architecture Knowledge: Deep understanding of microservices, API management, distributed systems, and messaging patterns.
• NFR Focus: Experience with performance tuning (e.g., JVM monitoring) and high-availability design.
• Communication: Proven ability to translate complex security/architectural concepts into business terms.
• Certifications (Preferred): CISSP, CISM, Azure Certified Solutions Architect, or equivalent.

1. Security Work & Dev Sec Ops (50%)

• Drive "Security by Design" principles throughout the software development life cycle (SDLC).
• Conduct threat modeling, secure code reviews, and vulnerability assessments.
• Implement security protocols (authentication/authorization, encryption) and ensure compliance (ISO, GDPR, SOC2).
• Embed Dev Sec Ops practices within CI/CD pipelines.
• Lead the investigation and mitigation of security incidents.

2. Solution Architecture & Technical Design (30%)-

• Lead end-to-end architecture design for complex distributed systems (microservices, cloud-native).
• Create and review Secured architectural design documents (HLD/LLD), ensuring alignment with business strategy.
• Oversee the AI model lifecycle—from experimentation to production deployment, including monitoring model performance, drift, and latency.
• Evaluate and select technology stacks, vendors, and frameworks.
• Conduct proof-of-concept (POC) initiatives to validate proposed technical solutions.
• Ensure systems are scalable, robust, and maintainable.

3. Non-Functional Requirements (NFRs) & Engineering Excellence (20%)

• Define and enforce NFRs, including performance, availability, scalability, and resilience.
• Set best practices for observability, monitoring, and alerting.
• Conduct performance tuning, load testing, and Chaos Engineering to ensure system stability.
• Develop engineering metrics to demonstrate improvements in team velocity and software quality.