AI Solution Architect

Requirements

• 7+ years of experience in software engineering and system design
• 3+ years in a technical leadership or architecture role
• Strong proficiency in Python
• Hands-on experience with AI/ML solutions (including LLMs / Generative AI)
• Proven experience designing distributed systems and integration-heavy solutions
• Experience with cloud platforms (AWS, GCP, or Azure)
• Hands-on experience with containerization and orchestration: Docker, Kubernetes, Helm
• Strong understanding of APIs, microservices, and system integration patterns
• Proven track record in consulting, pre-sales, and client-facing activities
• Strong communication skills and ability to work with both technical and non-technical stakeholders
• Advanced level of English

WILL BE A PLUS

• Experience with LLM-based solutions (RAG, AI agents)
• Hands-on experience with TensorFlow or PyTorch
• Background in Data Engineering or Big Data
• Cloud certifications

Personal Profile

• Ability to make and defend strategic technical decisions
• Strategic thinker with the ability to see the “big picture”
• Strong ability to bridge business needs with technical solutions
• High level of ownership and accountability
• Adaptability in dynamic environments
• Leadership through expertise and influence

Responsibilities

• Design scalable AI-driven solutions, ensuring performance, reliability, and maintainability
• Integrate multiple components (AI/ML, backend systems, third-party services) into a cohesive architecture
• Provide technical estimation, advisory services, PoCs, and support during pre-sale activities
• Collaborate with stakeholders to elicit and clarify product and technical requirements
• Partner with PMs to align architecture with project goals and constraints
• Translate complex business requirements into scalable and compliant technical architectures
• Define architectural standards, best practices, reference models, governance rules, CI/CD expectations, and operational guidelines
• Analyze existing client infrastructure and align new solutions accordingly
• Balance functional and non-functional requirements (performance, security, cost, scalability)
• Drive and justify key technical decisions based on trade-offs and alternatives