Data Scientist / AI Architect (Agentic AI & LLM Focus

Savvients, Inc
Los Angeles, United States of America
5 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Los Angeles, United States of America

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Cloud Engineering
Information Engineering
Identity and Access Management
Machine Learning
Data Logging
React
Retrieval-Augmented Generation
Large Language Models
Caching
Front End Software Development
Virtual Agents

Job description

We are engaging a hands-on Data Scientist / AI Architect to design and deliver agent-based, AI-enabled workflows integrated with enterprise systems. The role requires close collaboration with internal teams and business stakeholders to translate use cases into scalable, production-grade solutions., * Work closely with business stakeholders to:

o Translate business use cases into technical designs and acceptance criteria

o Communicate trade-offs across quality, cost, risk, and delivery timelines

Good to Have

Data Engineering for Retrieval-Based Systems

  • Design and manage retrieval pipelines to support grounding and context enrichment, including:

o Vector databases and similarity search

o Search and indexing systems

o Storage solutions for source data and embeddings

o Caching strategies for performance and scalability

Cloud-Native Delivery (AWS Preferred)

  • Deploy and manage AI/ML solutions on cloud platforms, with focus on:

o IAM and security best practices

o Scalability, resilience, and availability

o CI/CD pipelines and environment management

Integration & UX Enablement

  • Integrate AI solutions with enterprise tools via secure APIs and gateways

  • Collaborate with front-end teams (e.g., React) to enable seamless user experiences

Observability & Operations

  • Implement monitoring across workflows, including:

o Logging, metrics, and tracing for agent pipelines and model calls

Requirements

Hands-on experience in AI/LLM solution design and implementation

Strong understanding of AI/ML/LLM libraries used in projects

Experience with LLM fine-tuning (critical requirement)

Experience in RAG (Retrieval-Augmented Generation) architectures

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