Requirements:
BSc. in Electrical Engineering or equivalent with honor, MSc. or PhD - an advantage
8+ years experience in system architecture with a preference for experience in RF, high-performance systems or communication systems
4+ years experience in logic/ASIC architecture, design or verification
Experience working with multidisciplinary teams, guiding system, hardware, logic design and software development teams
Fast learner, strong technical skills, with capacity and the foundation to comprehend and derive conclusions from academic content
Ability to collaborate with global partners, vendors and customers
Strong interpersonal and communication skills
Background in quantum physics/quantum computing/physics - an advantage.

Requirements:
Qualifications / Experience / Technical Skills
Background in information systems, computing, engineering or equivalent industry experience preferred.

Have 10-15 years of experience in similar role

Technical background or a good understanding of technology and industry trends, especially in the app integration space

Strong working knowledge with APIs - RESTful

Sound knowledge of Data Structure - JSON

Previous coding experience / development background

Sound knowledge of any RDBMS

Knowledge of SOAP/XML is a plus

Comprehensive knowledge and hands-on experience in architecting solutions comprised of on-premise, cloud and hybrid scenarios

Experience working with cloud business apps like Workday / NetSuite / Salesforce / Servicenow / Marketo is a plus

Soft Skills / Personal Characteristics
Strong collaboration skills, ability to adapt to a dynamic start-up environment with a passion for making an impact

Strong critical thinking, analytical skills with an entrepreneurial and proactive mind-set

Ability to effectively prioritize tasks and manage time, even under high-pressure situations

Strong written and oral communication skills in English, with the ability to convey complex technical concepts effectively to a non-technical audience

Fast learner who can independently conduct extensive research, and synthesize ideas, information and options quickly

Be proactive about solving problems and be ready to take on additional initiatives and responsibilities as they emerge

Requirements:
10+ years of backend development experience, with at least 3+ years in an architectural or senior technical leadership role
Strong hands-on experience with Python in production environments
Proven experience designing and building distributed systems and microservices architectures
Extensive experience with AWS (S3, SNS, Lambda, Batch, DynamoDB, RDS, etc.)
Experience with containerization and orchestration technologies (Docker, Kubernetes, Helm, Terraform, ArgoCD)
Deep understanding of scalability, high availability, resilience, and system design principles
Experience with monitoring and observability tools such as Datadog
Proven track record of delivering large-scale, high-quality SaaS products
Strong understanding of LLM application architecture: prompt/version management, tool/function calling, structured outputs, retrieval-augmented generation (RAG), and agent/workflow patterns.
Proven ability to design for AI reliability and safety: guardrails, policy enforcement, content filtering, hallucination mitigation, and failure-mode design (fallbacks, safe defaults).
Experience with data governance and privacy for AI: PII handling, retention policies, redaction, tenant isolation, and secure logging/tracing in SaaS environments.
Ability to control cost/performance tradeoffs: model selection strategies, caching, batching, streaming, rate limits/quotas, and capacity planning for AI workloads.
Experience integrating AI services into distributed systems on AWS (e.g., scalable inference/RAG pipelines, async jobs, event-driven orchestration).
Advantage

Deep understanding of networking concepts
Experience with event-driven architectures
Experience working with enterprise customers and complex technical environments
Experience with vector databases / embedding pipelines and retrieval systems (indexing, chunking, relevance tuning).
Experience with model gateways / multi-provider routing, prompt registries, and feature flagging for model & prompt rollouts.
Familiarity with security & compliance considerations for AI (SOC2-ready controls, audit trails for AI actions, customer data boundaries).
Experience enabling AI-assisted SDLC / SDD practices (AI in design docs, code review, incident analysis) with governance and standards.