GenAI/Python Developer - AI/ML - Newyork, NY - Citi

Photon

United States

On-site

Who this role is best for

A natural match if you have hands-on experience with generative AI and multi-agent systems.

Best fit for

Professionals skilled in optimizing AI workflows for performance, cost, and scalability
— “Optimize GenAI workflows for latency, cost, scalability, and reliability”
Individuals with expertise in integrating commercial and open-source LLMs such as OpenAI and Mistral
— “Integrate and evaluate multiple commercial and open-source LLMs, including OpenAI, Anthropic, Llama, and Mistral”

Things to consider

This role is exclusively for full-time employees in the US, with no remote or contract options
— “This position is not available for independent contractors”
The role has a strict application deadline of 120 days after the posting date
— “No applications will be considered if received more than 120 days after the date of this post”

How to stand out

Highlight experience with multi-agent architectures and production deployment of AI workflows
— “design, build, and deploy production-grade Generative AI applications and intelligent agent-based solutions”
Demonstrate proficiency in fine-tuning LLMs for domain-specific use cases using PyTorch or TensorFlow
— “Fine-tune and customize LLMs for domain-specific use cases using PyTorch, TensorFlow, Hugging Face, LoRA, and QLoRA”
Showcase skills in building scalable backend services with FastAPI and asynchronous programming
— “Develop scalable and high-performance backend services and APIs using Python, FastAPI, and asynchronous programming”
Emphasize experience with vector databases and RAG systems in your project portfolio
— “Build and maintain advanced Retrieval-Augmented Generation (RAG) solutions using LlamaIndex and vector databases”
Include examples of prompt engineering that improved LLM response quality or application performance
— “Apply advanced prompt engineering techniques to improve LLM response quality and application performance”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

design and deploy AI applications
integrate and evaluate LLMs
optimize GenAI workflows

Typical background

AI/MLData ScienceSoftware Engineering

Skills & requirements

Required

PythonLanggraphLangchainLlamaindexRAGVector DatabasesLLM IntegrationMulti-agent Architectures

Preferred

Prompt EngineeringPyTorchTensorFlowHugging FaceLoraQlora

Stack & domain

PythonLanggraphLangchainLlamaindexVector DatabasesLLM IntegrationMulti-agent ArchitecturesFastapiAsynchronous ProgrammingPyTorchTensorFlowHugging FaceLoraQloraPrompt EngineeringMonitoring And ObservabilityDockerAWSAzureGCPLeadershipProblem-solvingCollaborationAIMLSoftware Development

About the role

Original posting from Photon

Job Description: GenAI/Python Developer – AI/ML
Role Overview
We are looking for an experienced GenAI/Python Developer to design, build, and deploy production-grade Generative AI applications and intelligent agent-based solutions. The ideal candidate will have strong expertise in Python, LangGraph, LangChain, LlamaIndex, RAG, vector databases, LLM integration, and multi-agent architectures.
The role requires hands-on experience building scalable AI solutions, integrating commercial and open-source LLMs, fine-tuning models, and optimizing GenAI applications for performance, latency, cost, reliability, and production scalability.
Key Responsibilities
Design, develop, and orchestrate sophisticated Generative AI workflows using LangGraph, LangChain, and multi-agent architectures.
Build and maintain advanced Retrieval-Augmented Generation (RAG) solutions using LlamaIndex and vector databases.
Design retrieval pipelines focused on improving the accuracy and relevance of LLM-generated responses.
Integrate and evaluate multiple commercial and open-source LLMs, including OpenAI, Anthropic, Llama, and Mistral, based on application, performance, and cost requirements.
Develop scalable and high-performance backend services and APIs using Python, FastAPI, and asynchronous programming.
Fine-tune and customize LLMs for domain-specific use cases using PyTorch, TensorFlow, Hugging Face, LoRA, and QLoRA.
Apply advanced prompt engineering techniques to improve LLM response quality and application performance.
Optimize GenAI workflows for latency, cost, scalability, and reliability.
Implement monitoring and observability for LLM applications using tools such as LangSmith and Langfuse.
Containerize AI applications and services using Docker and support production deployments through CI/CD pipelines.
Deploy and maintain GenAI solutions across cloud environments such as AWS, Azure, or GCP.
Collaborate with engineering, AI/ML, architecture, and product teams to convert business requirements into scalable AI solutions.
Troubleshoot and optimize production AI applications, APIs, retrieval pipelines, and model integrations.
Compensation, Benefits and Duration
Minimum Compensation: 155,000 USD
Maximum Compensation: 217,000 USD
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.

Source: Photon careers