Job Description
Role Summary:
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As AI Architect you are the design authority for Generative and Agentic AI solutions built on AI Next, from the first client workshop to production. You decide how a use case should be solved — model, retrieval, agent design, level of autonomy, guardrails — prove it with evaluations, and make sure it runs reliably, safely and at a known cost. The patterns you prove become AI Next reference architectures used by other teams.
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Your success in a year looks like 2-3 GenAI or Agentic solution taken from design to production meeting the agreed outcome under the cost targets with cost per transaction and AI performance tracked.
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Key Responsibilities:
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- Solution Architecture & Design:
- Design end-to-end architecture with key decision and trade-offs for Generative AI and Agentic AI solutions on the AI Next platform, covering LLM selection, RAG pipelines, agent orchestration, tool integration, and guardrails.
- Architect agentic and multi-agent workflows using frameworks such as LangChain, LangGraph, and Google ADK.
- Design backend and integration layers using Python, exposing AI capabilities as secure and scalable services.
- Choose simplest design covering deterministic workflow, single agent or multiagent with focus on right autonomy level, security, MCP integrations, auditability and human review required for the client problem statement.
- Design enterprise retrieval with ingestion, chunking, hybrid search, reranking and permission-aware access to data sources with knowledge refresh strategies.
- Structured evaluation and recommendation of foundation models (for example Claude, Gemini, and OpenAI models) and deployment options for client problem statements.
- Design IDP (Intelligent Document Processing) solution architecture end to end, combining document ingestion, classification, OCR and layout-aware extraction, LLM-based extraction, validation, human-in-the-loop review, and downstream integration (good to have).
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- Technical Leadership & Quality:
- Provide technical leadership and mentorship to Gen AI engineers, Python developers, and technology leads.
- Establish standards for prompt engineering, agent design, evaluation, and deployment of GenAI solutions.
- Conduct design and code reviews, and ensure reliability, security, scalability, and performance of AI solutions.
- Provide recommendations on optimizing cost per transaction adopting strategies like context management, routing, caching and batching.
- Troubleshoot and resolve technical issues in production AI systems.
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- Evaluation, Governance & Responsible AI:
- Define tracing, observability, cost, and latency monitoring approaches for LLM and agent-based solutions.
- Define and set up evaluations to support solutions with success metrics agreed by client stakeholders, datasets, harness and gating for automated tests
- Define rollout, rollback and fallback strategies with owing technical incidents and escalations.
- Assess ethical implications, data privacy, and security risks of GenAI deployments, and design appropriate policies, controls, guardrails and human review where errors are costly.
- Design for auditability in the context of client’s regulatory context while collaborating with security and compliance teams.
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- Client Advisory, & Pre-sales:
- Be the primary technical contact for client architects and business stakeholders, drive GenAI architecture workshops and explain trade-offs in business terms.
- Turn GenAI and agentic AI use cases into value cases with expected benefits, cost, risks, and define path to production.
- Support pre-sales activities by providing GenAI solution design, estimates, and assumptions.
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- Technical Leadership and Platform Impact
- Lead and mentor GenAI engineers, developers and technology leads enabling evaluation, design and operations.
- Turn proven patterns into AI Next reference architectures, templates and components.
- Assess new models, frameworks and standards against clear criteria before recommending adoption.
- Partner with product architecture, data, engineering, and security teams feeding them with gaps, client demands and failures thereby influencing the product roadmap.
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Locations -: Irving, Jersey City, Tampa
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Request to drop resume and contact details (WhatsApp number) below mail id
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