AI/ML Architect -

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Position: AI Architect

Location – Hybrid (2 Days onsite at nearby Deloitte office) –

Georgia - Atlanta, Texas – Austin, Dallas, Houston; Arizona –

Gilbert, Phoenix; Florida – Lake Mary, Orlando, Tampa; North Carolina – Charlotte; Massachusetts – Boston

Contract

VISAMust Haves

Experience in software engineering, AI/ML engineering, search engineering, or related technical roles---------- Years Experience building AI applications with LLMs, APIs, and orchestration or agent frameworks---------- Years . Experience with retrieval-augmented generation, semantic search, vector databases, or enterprise knowledge systems--------- Years . Strong programming skills in Java, Python, and/or another modern language ---------- Years . Experience designing and deploying production systems with cloud services, APIs, and data pipelines ---------- Years Ability to communicate effectively with technical and non-technical stakeholders---------- Years . Experience supporting financial advisors, wealth management platforms, or client/advisor digital experiences ---------- Years Familiarity with agent frameworks, tool-calling patterns, workflow orchestration, or multi-step reasoning systems ---------- Years Experience in regulated industries with privacy, security, compliance, and responsible AI requirements ---------- Years

Level Required for Primary Skill Expert (14+ years of experience - 10+ years of US experience mandatory)

Additional Details for Role Should be a hands on AI Engineer

Role Summary

We are seeking an AI Architect cum Engineer to design, build, and operationalize enterprise AI and agentic AI capabilities that support financial advisors in a wealth management environment. This role will focus on creating intelligent tools that help advisors access information faster, automate routine tasks, surface relevant insights, and deliver more personalized client experiences. This is an opportunity to shape the next generation of enterprise AI in a highly visible environment, where innovation, rigor, and business value all matter. The ideal candidate combines strong software engineering skills with hands-on experience developing AI solutions that are secure, scalable, and effective in a regulated financial services setting.

Key Responsibilities

Design and build enterprise AI applications that support advisor productivity, knowledge retrieval, and decision supportDevelop agentic AI capabilities that can assist with workflow execution, task automation, information synthesis, and next-best-action supportBuild retrieval-augmented generation solutions grounded in trusted enterprise content, client data, and advisor-facing knowledge sourcesIntegrate LLMs, APIs, databases, CRM platforms, and enterprise systems into seamless advisor workflowsImplement prompt, routing, tool-use, memory, and orchestration logic to support advisor-facing AI experiencesCreate evaluation frameworks to measure accuracy, relevance, latency, safety, and business valueCollaborate with product, architecture, compliance, legal, security, and business teams to deliver solutions aligned to wealth management requirementsApply engineering best practices for scalability, observability, auditability, and maintainabilitySupport governance, responsible AI controls, and documentation for AI and agentic systemsContribute to reusable patterns and accelerators for advisor-facing AI solutions

Required Qualifications

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or related field6+ years of experience in software engineering, AI/ML engineering, search engineering, or related technical rolesExperience building AI applications with LLMs, APIs, and orchestration or agent frameworksExperience with retrieval-augmented generation, semantic search, vector databases, or enterprise knowledge systemsStrong programming skills in Java, Python and/or another modern languageExperience designing and deploying production systems with cloud services, APIs, and data pipelinesAbility to communicate effectively with technical and non-technical stakeholdersExperience supporting financial advisors, wealth management platforms, or client/advisor digital experiencesFamiliarity with agent frameworks, tool-calling patterns, workflow orchestration, or multi-step reasoning systemsExposure to LLM evaluation, prompt engineering, observability, and experimentation practicesKnowledge of CRM, portfolio, planning, or client servicing workflows in wealth managementExperience in regulated industries with privacy, security, compliance, and responsible AI requirementsStrong engineering and problem-solving skillsAbility to translate business needs into practical AI solutionsCuriosity and adaptability in a fast-moving AI landscapeCollaborative mindset and clear communicationAttention to quality, reliability, and user trust