Agentic- AI Architect

WinWire

Santa Clara (CA)

On-site

USD 190,000 - 230,000

Full time

17 hours ago
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Qualifications

  • Degree in CS/AI/DS or related field
  • Advanced ML/DL/NLP coursework or certifications
  • Strong mathematical and statistical foundation
  • 6–10 years of AI/ML model development experience
  • 2–3 years Hands-on with LLMs, NLP, or speech/voice AI systems
  • 3–5 years deploying AI solutions in production

Responsibilities

  • Design, develop, and deploy advanced AI models to meet business requirements
  • Collaborate with data engineers, LLM Ops, and software teams for end-to-end solutions
  • Evaluate model performance, fine-tune, and ensure scalability and reliability
  • Research emerging AI/ML tech and propose innovative solutions
  • Mentor junior AI engineers and review code/models for best practices

Skills

Python
PyTorch
TensorFlow
LLMs
NLP
AWS Sagemaker
Azure ML
GCP AI
LangChain
API development
Model evaluation metrics
Bias detection
Realtime voice pipeline
Azure AI Speech
Containerization (AKS)

Education

Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field

Tools

LangChain
LangGraph
A2A
MCP
Multi agent orchestration

Job description

Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field

Advanced coursework or certifications in machine learning, deep learning, or NLP

Strong mathematical and statistical foundation

Experience Range
  • 6–10 years of experience in AI/ML/Deep Learning model development
  • 2-3 years Hands-on experience with LLMs, NLP, or speech/voice AI systems
  • 3-5 years of experience deploying AI solutions in production environments
Primary (Must have skills)* - To be Screened by TA Team
  • 5+ years of experience in Python, PyTorch, TensorFlow, or similar frameworks
  • 3-5 years of experience designing, training, and fine-tuning large language models or AI models, speech/voice AI systems, Realtime voice pipeline
  • 5 years of experience in cloud AI platforms (AWS Sagemaker, Azure ML, GCP AI)
  • 2+ years of experience in Agentic AI frameworks such as LangChain, LangGraph, A2A, MCP, and Multi agent orchestration
  • 2-3 years of experience Familiarity with model evaluation metrics, bias detection, and optimization
  • 5 years of experience in integrating AI models into applications via APIs or pipelines
  • 2-3 years experience in Azure services — Azure AI Speech and Translator, Azure OpenAI, AI Search, plus Container Apps/AKS, API Management, Event Hubs, Key Vault, and Application Insights
Key technical skills :
  • Design, develop, and deploy advanced AI models to meet business requirements
  • Collaborate with data engineers, LLM Ops, and software teams for end-to-end solutions
  • Evaluate model performance, fine-tune, and ensure scalability and reliability
  • Research emerging AI/ML technologies and propose innovative solutions
  • Mentor junior AI engineers and review code/models for best practices
Communication Skills:
  • Clearly explain AI concepts and model behavior to technical and non-technical stakeholders
  • Present complex model results in a concise and actionable manner
Interpersonal Skills:
  • Collaborate effectively with cross-functional teams
  • Provide constructive feedback and mentor junior team members
Problem-Solving and Analytical Thinking:
  • Identify bottlenecks in model performance and propose solutions
  • Troubleshoot deployment or integration challenges proactively
  • Analyze data patterns and model outputs to derive insights
  • Apply structured thinking to optimize AI workflows and pipelines
Task/ Work Updates
  • Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
  • Provides regular updates, proactive and due diligent to carry out responsibilities
Secondary Skills to be planned Post Hiring - Training Plan
  • Advanced LLM techniques, prompt engineering, and fine-tuning strategies
  • AI ethics, fairness, and responsible AI deployment
  • Continuous learning on emerging AI frameworks and architectures
  • LLMOps - layered evals (WER, entity F1, COMET), CI regression gates, tracing, cost-per-minute telemetry, model routing, and drift detection.
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