NEWPosted 3 hours ago

Job ID: JOB_ID_5655

Role Description

The AI Solutions Architect tasks include:

  • Architect & Design end to end Generative AI solutions by translating business requirements into scalable, secure, and cost effective technical architectures
  • Own solution design across the full lifecycle, including problem definition, architectural choices, data strategy, model selection, integration, deployment, and operations
  • Define and document solution architectures using architecture diagrams, sequence flows, deployment topologies, and technical design documents
  • Select appropriate GenAI approaches (RAG, fine tuning, prompt engineering, agentic workflows, routing, multimodal) based on accuracy, latency, cost, governance, and data constraints
  • Architect Retrieval Augmented Generation (RAG) solutions, including document ingesting, chunking strategies, embedding models, hybrid search, re ranking, caching, and freshness management
  • Design and implement agentic systems using tool/function calling, planner executor and multi agent patterns, with reliability, observability, and failure handling
  • Define prompt architecture patterns such as ReAct, Chain of Thought alternatives, structured output prompting, skill routing, and template versioning
  • Evaluate and integrate LLMs from both closed providers and open weight models, including model routing, fallback logic, and token cost optimization
  • Design fine tuning strategies (LoRA/QLoRA, PEFT, adapters) when prompting or RAG alone is insufficient, and define evaluation criteria for fine tuned models
  • Architect low latency, high throughput serving patterns using batching, caching, speculative decoding, quantization, and GPU/CPU routing
  • Design APIs, SDKs, and reusable platform components to enable consistent AI adoption across multiple teams and applications
  • Integrate GenAI solutions with enterprise systems including identity, authorization, data platforms, event streams, and front end applications
  • Define LLMOps practices covering prompt versioning, dataset management, experiment tracking, evaluation pipelines, regression testing, and observability
  • Establish monitoring and tracing for quality, hallucinations, safety violations, latency, throughput, and cost across AI workflows
  • Design safety, governance, and guardrail mechanisms including PII redaction, content filtering, prompt isolation, jailbreak defense, and audit logging
  • Conduct feasibility and risk assessments covering data readiness, compliance, security exposure, vendor lock in, performance, and operational risk
  • Lead technical discovery workshops and architecture reviews with product, engineering, data, and security stakeholders
  • Mentor engineers and teams on GenAI patterns, solution design tradeoffs, and architectural best practices
  • Evaluate tools, frameworks, and vendors, and drive build vs buy decisions based on technical and business constraints
  • Maintain reference architectures, design standards, architectural decision records (ADRs), and reusable blueprints
  • Drive continuous improvement of AI solution quality, reliability, scalability, and cost efficiency in production environments.

Preferred Technical Skills

  • Person should have excellent design experience with designing in-house systems (connecting with different ERP systems, connecting the data with other systems, designing data model) – minimum 10 years (5 years solution architect, 4-5 years Machine learning & AI experience)
  • GenAI frameworks: LangChain, LangGraph, AutoGen, Microsoft Agent Framework.
  • Model providers: Azure OpenAI, Anthropic, Google, AWS Bedrock, Snowflake Cortex AI, AgentCore
  • Retrieval & Vector DBs: OpenSearch, Pinecone, pgvector, Weaviate, GraphDBs (Neo4j, Neptune)
  • Serving Stack: vLLM, TGI, Ray Serve
  • LLMOps: Dataiku, MLflow, LangSmith, Weights & Biases
  • Safety: Azure AI Content Safety, Guardrails, NeMo Guardrails
  • Agents: LangGraph, AutoGen, CrewAI

Special Requirements

Visa: USC/GC; Location: Need Local with DL; Comments for Vendors: The preference is to have someone close to Princeton for 2X per week for whiteboarding sessions

Compensation & Location

Salary: $75 – $95 per year (Estimated)

Location: Princeton, NJ

Recruiter / Company – Contact Information

Email: yankagautam.rit@gmail.com

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