Build and ship production AI systems — LLM architectures, agents, and fine-tuned models — for large-scale engagements with partners across the USA, Israel, and Europe. We're growing our senior AI bench ahead of a wave of upcoming projects in Healthcare, FinTech, and Autonomous Systems.
We’re growing our senior AI bench ahead of a wave of large-scale projects with partners across the USA, Israel, and Europe. This is hands-on, production AI engineering — LLM architectures, autonomous agents, and fine-tuned models that ship and get measured by business outcomes, not benchmark scores.
You won’t spend your time on research without applications. Every engagement has a client depending on delivery, and you’ll own your domain end-to-end rather than work from a ticket queue.
What you’ll do
- Design and deploy scalable architectures built on Large Language Models
- Build and optimize AI agents that automate complex business processes
- Fine-tune models for domain-specific applications in Healthcare, FinTech, and Autonomous Systems
- Build reliable data pipelines and integrate AI components into production environments
- Define evaluation frameworks and quality metrics for AI features in production
- Advise on AI architecture tradeoffs — model selection, latency, cost, and reliability
The environment
Client engagements run small — typically 2–4 engineers. You’ll be the engineer clients talk to when something matters, working directly with technical decision-makers. Expect ambiguity, fast feedback loops, and real accountability for what you ship.
What we're looking for
- Expert-level Python — you write clean, production-grade code, not just notebooks
- Hands-on experience with PyTorch, TensorFlow, or JAX
- Working knowledge of frontier LLM APIs — OpenAI GPT-4, Anthropic Claude, and Llama 3
- Proficiency with LangChain or LlamaIndex orchestration frameworks
- Deep understanding of RAG (Retrieval-Augmented Generation) architectures
- Experience with vector databases — Pinecone, Milvus, Weaviate, or Chroma
- Strong command of Pandas, NumPy, and Scikit-learn
- Solid grasp of Transformer architectures and the Hugging Face ecosystem
- Practical cloud and MLOps experience — AWS or Google Cloud, Docker, and Kubernetes
- Upper-Intermediate to Advanced English — all documentation and client reviews are in English
Nice to have
- Experience fine-tuning models for domain-specific applications in regulated industries
- Background in autonomous navigation systems or mission logic
- Open-source AI contributions or a strong GitHub portfolio
- MLOps depth — model versioning, monitoring, and drift detection in production
What you'll get
- Real production AI work on modern stacks — not legacy maintenance or POC theater
- Sophisticated projects for international tech leaders across the USA, Israel, and Europe
- A senior, distributed engineering team where every peer has shipped software at scale
- Priority consideration for upcoming senior and lead engineering roles as projects ramp
- Fully remote, flexible hours, B2B contractor model with transparent rates
- Direct access to technical decision-makers — no PM or agency layer in between
Application sent. We'll be in touch within a few business days.
Don't see the right role?
We occasionally hire for roles we haven't posted yet. Send your background to career@insoftex.com and we'll keep it on file.