Full Stack AI Engineer

Title- Full Stack AI Engineer

Duration - 12 Months

Location - Sunnyvale CA 94085 (

Hybrid - come onsite as needed)

We are seeking a highly skilled

Founding AI Engineer

to partner with internal and cross-functional teams in defining AI product features, scope, and the platform's technical foundation.

Key Responsibilities:

Serve as a Founding AI Engineer, collaborating with cross-functional teams to define AI product features, scope, and overall technical architecture.

Design and implement generative AI systems, including:

Multi-agent workflows

LLM orchestration patterns

Tool-calling architectures

MCP integrations to connect models with enterprise APIs, tools, and data systems

Build scalable AI data pipelines to ingest heterogeneous data sources and implement AI-driven ETL processes, including:

Data cleaning

Normalization

Deduplication

Structured storage in production databases and vector indexes

Develop and optimize GenAI systems, including:

Fine-tuning LLMs and transformer models (e.g., LoRA/PEFT)

Prompt engineering

Designing RAG architectures for knowledge retrieval

Train, test, and deploy machine learning models, building:

Low-latency inference pipelines

Scalable AI services for real-time and batch workloads

Develop backend services and AI product interfaces, including:

APIs

Microservices

AI-powered dashboards

Ensure production reliability through:

Monitoring

Autoscaling

Performance optimization

Minimum Qualifications:

Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field

5+ years of experience building production AI or machine learning systems

Hands-on experience developing GenAI / LLM-powered applications using models such as GPT, Claude, or Gemini

Experience designing and deploying:

Agentic AI systems

MCP integrations

LLM orchestration workflows

Experience building:

RAG systems

Vector search solutions

AI knowledge discovery platforms

Experience with ML frameworks such as:

PyTorch

TensorFlow

scikit-learn

Experience designing scalable data pipelines and AI-driven ETL workflows

Experience building AI-powered dashboards or knowledge discovery interfaces

Preferred Qualifications:

Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field

Experience fine-tuning transformer models using techniques such as LoRA or PEFT

Hands-on experience with:

Cloud platforms (e.g., AWS)

Containerization technologies (e.g., Docker)