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.