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Software Developer/Engineer (Mid Level experience)

TechArmy
Posted 2 months ago, valid for 13 days
Location

Philadelphia, PA, US

Salary

Competitive

Contract type

Contract

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Sonic Summary

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  • The position is a contract role based in Philadelphia with a hybrid work model requiring a minimum of three days in the office.
  • Candidates should have hands-on experience deploying open-source LLMs like Meta Llama 3 and Mistral, along with strong Python proficiency for LLM inference and prompt engineering.
  • Practical knowledge of open-source vector databases and the implementation of Retrieval-Augmented Generation (RAG) pipelines is essential.
  • The role offers a competitive salary of $150,000 per year and requires at least 5 years of relevant experience in the field.
  • Experience in regulated environments and familiarity with Docker and Kubernetes is considered a plus.

Position Type: Contract

Location: Philadelphia | Work Mode: Hybrid, minimum 3 days in the office

Interview Schedule: 1st interview, 1-hour, in-person; 2nd interview, 1-hour, in-person

Consultant Requirements – On-Prem LLM & Vector DB Implementation

Core Experience

Hands-on experience deploying open-source LLMs such as Meta Llama 3 and Mistral / Mixtral in on-prem or private environments

Strong proficiency in Python for LLM inference, prompt engineering, and integration

Experience with CPU-based inference, model quantization, and performance tuning

Vector Databases & RAG

Practical experience with open-source vector databases such as Qdrant, Chroma, Milvus, or pgvector

Proven implementation of Retrieval-Augmented Generation (RAG) pipelines

Experience generating and managing embeddings and metadata filtering

Security & Governance

Understanding of data privacy, air-gapped deployments, and enterprise security requirements

Experience implementing access controls and audit logging

Nice to Have

Experience with LangChain or LlamaIndex

Exposure to Rust, Go, or C++ for high-performance services

Familiarity with Docker and Kubernetes for on-prem deployments

Knowledge of inference frameworks (e.g., vLLM, llama.cpp, Hugging Face Transformers)

Prior work in regulated or enterprise environments

Deliverables

Reference architecture and deployment guidance

Working prototype (LLM + vector DB + RAG)

Documentation and knowledge transfer to internal teams




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