Python + Gen AI Developer - New York

Posted 14 Hours Ago
2 Locations
In-Office or Remote
56K-196K Annually
Senior level
Agency • Information Technology
The Role
Build, optimize, and deploy production-grade generative AI applications. Design multi-agent systems and LangGraph workflows, implement advanced RAG with LlamaIndex and vector DBs, fine-tune and host LLMs, integrate/swap commercial and open-source models, and deliver scalable FastAPI/async backends with Docker, monitoring, and CI/CD.
Summary Generated by Built In

Role Summary:
We are seeking a Generative AI Engineer to build, optimize, and scale production-ready AI applications. You will design complex multi-agent systems, implement advanced RAG pipelines, and manage the deployment of both frontier and local LLMs. The ideal candidate blends deep machine learning expertise with modern software engineering practices.


Technical Stack:

LLMs: Gemini, OpenAI, Claude, Llama, and Local Model deployment.

Frameworks: LangChain, LlamaIndex, and Hugging Face.

Orchestration: LangGraph and Multi-Agent Systems (MAS).

Development: Python, FastAPI, and Asynchronous Programming.

RAG & Data: PostgreSQL, Vector Databases, and Advanced Retrieval strategies.

ML/DL: PyTorch, TensorFlow, and Model Fine-tuning.

Deployment: Docker, Production API management, and LLM monitoring.

Tools: Prompt Engineering, Workflow Design, and GenAI Optimization.


Key Responsibilities:

Develop and orchestrate sophisticated AI workflows using LangGraph and multi-agent architectures.

Build and maintain Advanced RAG systems utilizing LlamaIndex and vector databases for high-accuracy retrieval.

Integrate and swap diverse LLMs (commercial and open-source) based on performance and cost requirements.

Design and deploy high-performance, scalable backend services using FastAPI and Async Python.

Fine-tune large language models (LLMs) using PyTorch/TensorFlow to improve domain-specific performance.

Optimize GenAI workflows for latency, cost, and reliability using advanced prompt engineering and monitoring tools.

Containerize and deploy AI services via Docker to production environments.


Required Qualifications:

7+ years of hands-on experience building and deploying GenAI applications in a production setting.

Strong proficiency in Python and the modern AI library ecosystem (LangChain, LlamaIndex, etc.).

Experience with vector search, embedding models, and advanced data retrieval patterns.

Knowledge of model fine-tuning techniques and local LLM quantization/hosting.

Familiarity with production-grade monitoring, API security, and CI/CD for ML.

Compensation, Benefits and Duration

Minimum Compensation: USD 56,000
Maximum Compensation: USD 196,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post

Skills Required

  • 7+ years building and deploying GenAI applications in production
  • Strong proficiency in Python and asynchronous programming
  • Experience with LangChain, LlamaIndex, and the modern AI library ecosystem
  • Experience designing and orchestrating multi-agent systems and LangGraph workflows
  • Experience with vector databases, vector search, embedding models, and advanced retrieval patterns
  • Experience fine-tuning LLMs using PyTorch and/or TensorFlow
  • Knowledge of local LLM quantization, hosting, and swapping between commercial and open-source models
  • Experience building high-performance backends with FastAPI and async Python
  • Experience containerizing and deploying services with Docker and managing production APIs
  • Familiarity with production-grade monitoring, API security, and CI/CD for ML
  • Experience with prompt engineering, workflow design, and GenAI optimization for latency and cost
  • Experience with PostgreSQL or relational data integration in RAG pipelines
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The Company
HQ: London
5,017 Employees
Year Founded: 2007

What We Do

Photon.com has emerged as one of the world’s largest and fastest-growing Digital Agencies. We work with 40% of the Fortune 100 on their Digital initiatives and are known for our ability to integrate Strategy Consulting, Creative Design, and Technology at scale. Please visit www.photon.com to learn more about us, how we work, and our customer case studies. Digital Transformation Starts Here.

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