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Python Developer (GenAI)

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Onsite

Python Developer (GenAI)

Technology Ventures

Python Developer (GenAI)

Skills

DockerReactPythonPostgreSQLGraphQLGitLabJenkinsData AnalysisAIAWSJiraConfluenceNLP / Natural Language ProcessingFastAPI

17 days ago

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Important information


Contract type:

Freelance / Contract

Location:

Reston, VA, USA

Work mode:

Onsite

Published on:

2 October 2026

What they need


Senior Full Stack GenAI Engineer with 10+ years of experience to design and build agentic AI solutions that automate enterprise workloads and business processes.

The ideal candidate will have strong expertise in Python-based backend development, LLM-powered applications, cloud-native deployment, vector databases, and modern DevOps practices. This role involves building end-to-end AI systems that integrate with enterprise platforms, automate workflows, and deliver production-grade AI applications.

Key Responsibilities

  • Design and develop agentic AI applications that automate enterprise workflows and decision-making processes.

  • Build scalable backend services using Python, FastAPI, and Pydantic.

  • Develop and deploy LLM-powered applications using models such as GPT and Claude.

  • Build AI agents and orchestration workflows using LangChain or Strands.

  • Implement Retrieval Augmented Generation (RAG) solutions using vector databases (pgvector, Pinecone, Weaviate).

  • Perform data analysis, preparation, and curation to build high-quality datasets for AI and knowledge retrieval systems.

  • Design and implement document ingestion pipelines for enterprise knowledge sources such as SharePoint, Confluence, and Jira.

  • Deploy AI workloads on AWS (Bedrock, ECS Fargate, S3) with proper security and scalability practices.

  • Develop and integrate enterprise APIs using REST, GraphQL, WebSockets, and web services.

  • Implement secure authentication and authorization using Ping Identity, OAuth2, OIDC, and SSO.

  • Build user interfaces for AI applications using ReactJS or Streamlit.

DevOps & Deployment

  • Build and manage CI/CD pipelines using Jenkins or GitLab.

  • Implement GitOps practices for automated deployments.

  • Containerize applications using Docker and deploy to cloud platforms.

  • Implement security best practices, vulnerability scanning, dependency management, and container security.

Required Skills

Backend & APIs

  • Python

  • FastAPI

  • Pydantic

  • REST APIs, GraphQL, WebSockets

GenAI & Agent Frameworks

  • LLMs (GPT, Claude)

  • LangChain or Strands

  • Retrieval Augmented Generation (RAG)

  • NLP (Natural Language Processing)

Data & AI Pipelines

  • Data analysis, data preparation, and data curation

  • Document ingestion and knowledge base creation

  • Embeddings and semantic search

Vector Databases

  • pgvector

  • Pinecone

  • Weaviate

Cloud & Platforms

  • AWS (Bedrock, ECS Fargate, S3, Guardrails)

Databases

  • PostgreSQL

  • DynamoDB

Security & Identity

  • Ping Identity

  • OAuth2 / OIDC

  • SSO, Authentication & Authorization

DevOps

  • Jenkins

  • GitLab

  • GitOps practices

  • Docker containerization

  • Security vulnerability mitigation

Frontend

  • ReactJS

  • Streamlit

Enterprise Tools

  • Portkey (AI Gateway)

  • Apigee (API Gateway)

  • Jira, Confluence, SharePoint

________________________________________

Preferred Qualifications

  • Experience building AI agents for enterprise automation.

  • Experience implementing AI guardrails and LLM governance frameworks.

  • Experience building enterprise copilots or knowledge assistants.

  • Familiarity with LLMOps and AI observability platforms.

________________________________________

What We're Looking For

  • Strong full stack engineering mindset with GenAI expertise.

  • Experience building production-grade AI systems.

  • Ability to work across AI, backend, cloud, and DevOps stacks.

  • Passion for building automation solutions powered by agentic AI.

________________________________________

Experience

  • 10+ years of software engineering experience

  • 3+ years hands-on experience delivering GenAI-based enterprise applications

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