AI Python Engineer – Public-Safety Solutions

Reposted One Month Ago
28 Locations
Remote
7K-10K Annually
Senior level
Artificial Intelligence • Security • Software
The Role
Design and deploy AI microservices and LLM-powered applications using Python, REST/gRPC, Docker, and Kubernetes. Build RAG, hybrid search, agent, fine-tuning, quantization, evaluation, and prompt-guardrail systems. Monitor model quality, latency, cost, and security while integrating databases and SIEM/SOC platforms. Establish MLOps, testing, observability, and compliance standards for high-security public-safety environments. Collaborate with security teams on CJIS and FedRAMP audits, with optional travel to Japan and the United States.
Summary Generated by Built In

📍 Location: Remote (PL / EU)

💰 Compensation (B2B): To be agreed (proposed 25–35k PLN net B2B). All travel expenses covered.

📝 Contract Type:Full-time • B2B

📈 Seniority Level: Senior / Principal

🧰 Tech Stack Tags:

Python · FastAPI · Docker · K8s · LangChain · LlamaIndex · LLM · HuggingFace · Cursor · Windsurf · Qdrant · gRPC · Azure/AWS · MLOps

🏢 About Us

Join a team building some of the most advanced AI systems in the world.

We develop core IT solutions supporting federal agencies and law enforcement in the U.S., where technology truly makes a difference.

Our systems leverage:

  • the latest advancements in natural language processing (NLP),

  • multimodal AI analyzing text, images, and sound,

  • and intelligent decision automation enabling real-time response.

These are systems that detect threats faster, analyze evidence more efficiently, and support humans in making the right calls—when every second counts.

Our solutions run in high-security environments:

air-gapped or in private cloud deployments, compliant with CJIS and FISMA standards—ensuring full data privacy and integrity.

🎯 What You’ll Do
  • Design and maintain microservices (REST/gRPC) exposing AI models via API

  • Package and deploy models (vLLM, Ollama, HF Transformers) with Docker + CI/CD

  • Build advanced retrieval pipelines combining RAG and hybrid dense‑sparse search (BM25 + embeddings, multi‑vector, re‑ranking) using Qdrant/Weaviate/Pinecone/Elasticsearch and frameworks like LangChain, LlamaIndex, LangGraph.

  • Perform fine-tuning, quantization, and RLHF/RLAS on Llama 3/4, Qwen, Mistral (datasets, experiments, evaluation)

  • Create prompt tooling (templates, guardrails, eval harnesses) and benchmarking aligned with CJIS requirements

  • Implement model quality monitoring (latency, token cost, hallucination rate) and security policies (Guardrails AI, LlamaFirewall)

  • Integrate with SIEM/SOC systems and databases (Elasticsearch, PostgreSQL)

  • Co-develop MLOps standards, testing, logging, observability (Prometheus, Grafana)

  • Work with security teams on audits and certifications (CJIS, FedRAMP)

  • Optional business travel to Japan (Roppongi Hills, Tokyo) and the United States (Irvine, California).

🔧 Must-Haves
  • 8+ years Python 3.x (FastAPI / Django / Flask)

  • 2+ years hands-on with LLMs (OpenAI, Azure OpenAI, Anthropic) and self-hosted models (Llama 3/4, Mistral)

  • Experience building RAG, hybrid search systems and agents using LangChain / LlamaIndex / LangGraph

  • Experience with Vector DBs (Qdrant / Milvus / Pinecone) and agent frameworks (LangGraph, CrewAI)

  • Docker (multi-stage) + Kubernetes, including Helm or Kustomize

  • Strong understanding of HTTP/REST, CI/CD (GitHub Actions / GitLab CI), and security-by-design principles

🌟 Nice-to-Haves
  • Helm / Kustomize, Terraform

  • Azure (AKS, OpenAI Service) or AWS (SageMaker, Bedrock)

  • gRPC, event-driven architecture (Kafka / RabbitMQ)

  • Experience with Guardrails AI, LlamaFirewall, PyTorch Lightning

🤝 Soft Skills
  • Technical ownership and attention to documentation

  • Clear communication in a distributed team (ENG B2+)

  • Focus on security, performance, and regulatory compliance

🎁 What We Offer
  • Real impact — your code will support law enforcement in fighting crime and saving lives

  • 100% remote work + flexible hours (core overlap 10:00–15:00 CET)

  • Access to a private LLM environment + GPU cluster (for feature-flagged demos)

  • Training budget + participation in international Python/AI conferences

Skills Required

  • 8+ years of experience with Python 3.x and frameworks such as FastAPI, Django, or Flask
  • 2+ years of hands-on experience with LLMs, including OpenAI, Azure OpenAI, Anthropic, and self-hosted models
  • Experience building RAG and hybrid search systems and agents using LangChain, LlamaIndex, or LangGraph
  • Experience with vector databases such as Qdrant, Milvus, or Pinecone
  • Experience with agent frameworks such as LangGraph or CrewAI
  • Experience with Docker, including multi-stage builds, and Kubernetes
  • Experience with Helm or Kustomize
  • Strong understanding of HTTP and REST
  • Experience with CI/CD using GitHub Actions or GitLab CI
  • Understanding of security-by-design principles
  • Helm, Kustomize, or Terraform experience
  • Azure experience, including AKS or OpenAI Service, or AWS experience, including SageMaker or Bedrock
  • Experience with gRPC and event-driven architecture using Kafka or RabbitMQ
  • Experience with Guardrails AI, LlamaFirewall, or PyTorch Lightning
  • English communication at B2+ level
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The Company
HQ: Luzianes-Gare
50 Employees
Year Founded: 1992

What We Do

DATAPILOT develops mobile and digital forensic solutions for law enforcement and government agencies. Its platform and devices acquire evidence from cell phones, tablets, CCTV, gaming systems, VR headsets, infotainment systems, smart TVs, and other digital devices, then support reporting, evidence tagging, analysis, and intelligence workflows. The company emphasizes affordable, easy-to-use solutions for collecting forensically sound digital evidence.

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