NEWPosted 4 hours ago

Job ID: JOB_ID_3977

Role:

AI Technical Architect

Location:

Richardson, TX Onsite Candidate should go to the office 3 days a Week 

Key Responsibilities:

  • Define AI/ML reference architecture and solution blueprints (batch/streaming ML, LLM+RAG, multimodal).
  • Lead endtoend solution design: data ingestion feature stores model training inference monitoring.
  • Architect LLM applications (chatbots, copilots, agents, summarization, classification) with RAG, evaluation, safety, and guardrails.
  • Own MLOps/LLMOps: CI/CD for models, model registry, feature store, lineage, observability, drift and cost monitoring.
  • Choose the right cloud and runtime (managed services vs. selfhosted; GPU/CPU; serverless vs. containerized).
  • Establish security, compliance, and governance (PII handling, encryption, auditability, Responsible AI).
  • Collaborate with product and business stakeholders to translate requirements into architectural decisions and delivery plans.
  • Perform technical spikes/POCs, benchmark models/infrastructure, and lead Architecture Reviews.
  • Create and maintain standards, patterns, and reusable components; mentor engineers across teams.
  • Drive performance & cost optimization (throughput/latency/SLA/SLO; caching; quantization/distillation; autoscaling).
  • Support vendor/product evaluations (cloud AI services, vector DBs, orchestration frameworks, monitoring).

Required Qualifications:

  • Bachelors/Masters in Computer Science, Engineering, Data/AI or related field.
  • 15+ years of overall engineering experience with 4+ years in AI/ML solution architecture.
  • Proven experience designing and deploying AI systems in production at scale (LLM and/or classical ML).
  • Strong handson proficiency in Python and cloud-native architectures (AWS/Azure/GCP).

MustHave Technical Skills:

AI/ML & LLM Architecture

  • Designing LLM/RAG systems: retrieval pipelines, chunking strategies, embeddings, reranking, prompt/response orchestration, evaluation and safety.
  • Model life cycle: finetuning, PEFT/LoRA, quantization/distillation, latency & cost management.
  • Classical ML/NLP: feature engineering, model selection, training, crossvalidation, metrics, A/B testing.

MLOps / LLMOps

  • CI/CD for ML (model/version promotion), feature stores, model registry, lineage and drift detection.
  • Inference stacks: Torch/TensorFlow, vLLM/TGI/ONNX, GPU orchestration, autoscaling, APM.
  • Pipelines & orchestration: Airflow, Kubeflow, MLflow, SageMaker, Vertex AI, Azure ML.

Keywords:

continuous integration continuous deployment artificial intelligence machine learning golang Texas

Compensation & Location

Salary: $65 – $70 per year (Estimated)

Location: Richardson, TX

Recruiter / Company – Contact Information

Email: _khan@aesincus.com

Interested in this position?
Apply via Email

Recruiter Notice:
To remove this job posting, please send an email from
_khan@aesincus.com with the subject:

DELETE_JOB_ID_3977

to delete@join-this.com.