Senior Specialist - Architecture

The AI Architect will play a pivotal role in leading the design and implementation of scalable, secure, and maintainable technology solutions that integrate pragmatic AI acceleration into software engineering practices. This position demands strong architectural expertise across cloud-native platforms, APIs, microservices, front-end frameworks, and integration patterns. The ideal candidate will possess hands-on experience with Claude AI prompt engineering, large language model (LLM) enabled workflows, and responsible AI adoption throughout the software development lifecycle (SDLC).

Key Responsibilities

- Demonstrate deep expertise in the Agentic ecosystem, covering both tooling and technology aspects.
- Lead system design efforts involving polyglot technology stacks.
- Drive architecture ideation aligned with organizational policies on AI SDLC governance and security.
- Incorporate AI components effectively into business solutions and software engineering processes.
- Define end-to-end technical architecture spanning front-end, APIs, microservices, integration, data, and deployment layers. Develop solution blueprints, reference architectures, design patterns, and engineering guardrails for use by multiple teams.
- Create blueprints for goals planning, model optimization, handoffs, skills output, and validation processes.
- Guide engineering teams on design decisions related to scalability, resilience, security, performance, maintainability, and observability.
- Integrate AI-assisted engineering practices into the SDLC, including requirements refinement, design exploration, code generation support, test acceleration, and documentation.
- Evaluate the suitability of Claude AI and other LLM capabilities to enhance software engineering productivity, knowledge management, and delivery acceleration.
- Collaborate closely with business analysts, full-stack engineers, quality engineers, and delivery leaders to translate business objectives into robust technical solutions.
- Review architecture and code to ensure compliance with standards, reusable patterns, security expectations, and cloud-native engineering principles.
- Support API strategy, event-driven architecture, integration design, data movement patterns, and service contract governance.
- Mentor engineers and technical leads on modernization, AI-augmented delivery, and pragmatic architecture practices.

Required Qualifications

- Extensive experience (12+ years) in architecture across Angular or comparable front-end frameworks, API platforms, and modern service-oriented architectures.
- Deep expertise in the Agentic ecosystem, including tooling and technology.
- Strong system design skills with polyglot technology environments.
- Proven ability to ideate architecture based on AI SDLC governance and security policies.
- Hands-on knowledge of cloud-native design principles using Docker, Kubernetes, CI/CD pipelines, and infrastructure-aware engineering practices.
- Experience with microservices, REST APIs, messaging, and event-driven patterns using platforms like Kafka or equivalents.
- Solid understanding of security, identity and access control, secrets management, logging, observability, monitoring, and resilience patterns.
- Skilled in defining engineering standards for code quality, automated testing, deployment automation, release governance, and operational readiness.
- Practical knowledge of LLM-enabled solution patterns, including prompt design, context management, retrieval-augmented approaches, tool-assisted workflows, and human-in-the-loop validation.
- Familiarity with responsible AI practices such as output verification, governance, privacy, security, auditability, and safe enterprise data usage.
- Strong proficiency in using Claude AI for architecture ideation, design comparison, prompt engineering, SDLC acceleration, and productivity improvements.
- Ability to create structured prompts for requirements analysis, architecture option generation, risk identification, design documentation, and workflow enhancement.
- Awareness of GenAI or LLM frameworks, model APIs, orchestration patterns, data grounding, prompt lifecycle management, and evaluation methodologies.
- Capability to assess trade-offs involving cost, reliability, complexity, maintainability, and delivery speed.
- Mandatory skills include Agentic AI, architecture patterns and styles, Java, Python, software engineering, and design architecture.

Preferred Qualifications and Additional Skills

- Experience with agent development and frameworks, Agentic AI systems design, and Agentic API orchestration.
- Knowledge of tooling such as function calling, planning, memory management, AI governance, compliance, safety, security analysis, and AI security engineering.
- Familiarity with AI strategy, AI-assisted development and coding, vector store databases, retrieval-augmented generation (RAG), and Angular.
- Expertise in application security frameworks, threat modeling, secure SDLC, DevSecOps, and application security architecture review.
- Proficiency in cloud platforms and services, cloud solution architecture, Docker, Kubernetes, Git, GitHub Advanced Security, GitHub Copilot, HTML5, JavaScript, TypeScript, SpringBoot, and Bootstrap/CSS.
- Experience with LLM architecture synthesis, observability, monitoring metrics (drift, quality, hallucination), LLMOps, MCP servers, microservices, MS SQL Server, multi-agent orchestration, process improvement, and operational consulting.
- Strong leadership skills and experience mentoring teams in AI-augmented delivery and pragmatic architecture practices.

This role offers the opportunity to work at the forefront of AI-driven software architecture, combining deep technical expertise with innovative AI integration to accelerate engineering productivity and deliver robust, future-ready solutions.