Ai Architect (SRK20ST RM 4395)

Position: Ai Architect (SRK20ST RM 4395)

Sponsorship is not provided. Hybrid mode

Requirements:

• Design, develop, and deliver AI-enabled features and agent-driven workflows that solve real business challenges.
• Build resilient production systems leveraging cloud-native AI services, agent frameworks, and LLM APIs (e.g., OpenAI, Anthropic).
• Implement agent-based architectures encompassing reasoning loops, guardrails, observability, and operational controls.
• Collaborate closely across teams to gather requirements and iterate quickly, employing agile and DevOps principles.
• Champion quality and security with a “shift-left” testing mindset, ensuring compliance and reliability in AI solutions.
• Monitor AI system behaviour post-deployment, clearly communicating limitations, risks, and performance.
• Use AI-assisted coding tools to boost developer productivity and code quality within the team.
• Engage in continuous improvement through code reviews, evaluation design, and metrics-driven iteration.

Skills you need:

• Strong software engineering background, with Python‑first development experience.
• Proven experience building production systems that integrate with LLM API services e.g. OpenAI API services.
• Hands‑on experience with agentic or tool‑using AI systems, including orchestration, memory, and toolchains.
• Experience designing and using evals to measure model quality, reliability, safety, and regression.
• Comfort working with cloud managed AI services and modern agent frameworks.
• Familiarity with RAG workflows, vector stores, embedding design, and latency/cost trade‑offs.
• Experience thinking about (and engineering for) failure modes, guardrails, operational reliability, and user impact.

Experience and qualifications:

• You must have experience the transitioning from traditional software engineering to AI-first environments.
• Exposure to AWS Bedrock, Azure Foundry, or similar cloud AI agent platforms.
• Knowledge of interoperability standards (A2A, MCP).
• Experience with containerisation (Docker, Kubernetes) and modern DevOps tooling.
• Active contributor to engineering communities, continuous learning, and knowledge sharing.
• Wealth management experience is a must have

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