Technical Architect - Artificial Intelligence

Role summary :

We are hiring a Technical Architect to design and lead production-grade AI and agentic systems for regulated industries, with a primary focus on healthcare and a secondary focus on fintech. You will own end-to-end architecture for our internal platforms and act as the senior technical voice in client engagements. The role is moderately hands-on : you will build proofs of concept, review code, and guide engineering teams, without direct reports.

Key responsibilities :

Architecture and system design :

• Define target-state architecture for AI-enabled platforms, including current-state assessment, target state and migration plan.
• Design scalable, resilient distributed systems : microservices, event-driven patterns, APIs, data pipelines and caching.
• Make and document build-vs-buy, technology and trade-off decisions through architecture decision records.
• Keep designs cloud-agnostic and portable across AWS, Azure and GCP.

AI and agentic systems :

• Architect agentic workflows and multi-agent systems, including orchestration, tool use, memory and state management.
• Design retrieval-augmented generation (RAG) pipelines over structured and unstructured data.
• Build guardrails into every agent : scope limits, output validation, hallucination checks, fallback paths and human-in-the-loop review for high-risk actions.
• Set up evaluation, observability and cost/latency monitoring for LLM-based systems in production.
• Select and evaluate LLMs, agentic frameworks and vector stores against business and compliance needs.

Security, privacy and compliance :

• Embed privacy-by-design into data flows : data minimization in prompts and agent payloads, encryption, access control and audit trails.
• Partner with Security, Compliance and Legal to meet regulatory requirements in healthcare and financial services.
• Contribute to compliance documentation and audits.

Client and stakeholder engagement :

• Lead technical discovery and solution workshops with clients.
• Translate business and regulatory needs into technical designs, estimates and delivery roadmaps.
• Present architecture and trade-offs clearly to executives and engineers alike.
• Support pre-sales with solution proposals and technical responses.

Technical leadership :

• Build proofs of concept to validate architecture choices before full delivery.
• Review code and designs to enforce standards for quality, security and performance.
• Mentor engineers and tech leads; raise the team's AI engineering capability.

Required qualifications :

• 10+ years of overall experience in software engineering and architecture.
• 8+ years of hands-on core development in one or more languages such as Python, Java, C#/.NET, Go or TypeScript/Node.js.
• 3+ years designing and delivering AI/ML solutions, including LLM-based applications and AI architecture.
• Production experience with at least one agentic framework, including multi-agent orchestration, tool/function calling and agent memory. Systems must have run in production with real users, not only prototypes.
• Strong system design skills : distributed systems, microservices, event-driven architecture, API design, scalability, fault tolerance and observability.
• Working knowledge of RAG, embeddings and vector databases, prompt engineering and LLM evaluation methods.
• Experience with containers, Kubernetes, CI/CD and infrastructure as code on at least one major cloud.
• Professional experience in the healthcare or fintech domain (see Domain expertise).
• Bachelor's degree in Computer Science, Engineering or a related field, or equivalent experience.

Domain expertise :

Candidates must have worked in healthcare or fintech. Healthcare experience is preferred; fintech candidates with strong regulated-domain experience are welcome.

Healthcare (preferred) :

• Designing HIPAA-compliant architectures, including PHI handling, de-identification, consent and audit logging.
• Interoperability standards such as FHIR (R4), HL7 v2 and CDA, and integration with EHR/EMR systems.
• Healthcare authentication patterns such as SMART on FHIR, OAuth 2.0 and SAML.
• Familiarity with clinical, payer or provider workflows (claims, prior authorization, care management, clinical documentation).
• Awareness of frameworks such as HITRUST and SOC 2, and of regulations on AI in clinical settings.

Fintech :

• Designing PCI DSS-compliant systems, including scope reduction, tokenization and encryption of sensitive data.
• Knowledge of the payments or lending lifecycle : authorization, settlement, reconciliation, disputes and idempotency.
• Guardrails for AI agents that touch money movement, such as deterministic handoffs and human approval for financial actions.
• Awareness of KYC/AML, GDPR, SOC 2, model risk management and AI regulations such as the EU AI Act.

Preferred qualifications and soft skills :

Nice to have :

• Experience with agent interoperability standards such as Model Context Protocol (MCP) or agent-to-agent protocols.
• MLOps/LLMOps experience : model deployment, versioning, monitoring and prompt management.
• Experience with responsible AI practices : bias testing, explainability and AI governance frameworks.
• Cloud architecture certification (AWS, Azure or GCP).
• Experience in consulting or client-facing delivery, including estimation and fixed-scope engagements.

Soft skills :

• Clear written and verbal communication, from executive summaries to detailed technical specs.
• Sound judgment in high-stakes, cross-functional discussions with Security, Compliance and Legal.
• Comfort with ambiguity and the ability to turn vague requirements into concrete designs.
• A mentoring mindset and the ability to lead through influence rather than authority.