Full Time

Python/AI Engineer

Matlen Silver
Contract
Financial Services, Banking, and Capital Markets
New York, United States
???* / year

Job Description

Python/AI Engineer

Python Developer
AI Engineer Project Details

  • Develop core Agent Runtime capabilities and reusable platform services.
  • Build agent orchestration, memory management, context management, and runtime execution capabilities.
  • Develop APIs, SDKs, and platform components for scalable AI adoption.
  • Implement platform guardrails, security controls, governance, and policy enforcement capabilities.
  • Build testing, benchmarking, evaluation, and observability frameworks.
  • Troubleshoot runtime, performance, integration, scalability, and operational issues.
  • Conduct proof-of-concepts and evaluate emerging AI technologies.
  • Participate in full SDLC activities including requirements analysis, design, development, testing, and deployment.
  • Conduct code reviews and contribute to engineering standards and best practices.

Must Haves / Required Skills:
7 years of experience minimum, internships do not count

  • Python.
  • FastAPI.
  • Asynchronous programming (async/await).
  • API design and integration.
  •  MongoDB.
  • Redis.

  • Skills / Experience That Are A Plus
    “nice to have”, but not necessarily required:

  • LangChain.
  • LangGraph.
  • Dependency injection.
  • Background processing.
  • Automated testing (unit, integration, regression, performance, evaluation).
  • CI/CD pipeline development.
  • Enterprise application development.
  • Security controls, governance, policy enforcement, and guardrails.
  • Look for candidates with enterprise platform engineering, API development, testing automation, CI/CD, and distributed systems experience.
  • Experience building reusable frameworks, SDKs, platform services, and developer tooling is highly relevant.
  • AI agent framework experience (LangChain, LangGraph, etc.) is beneficial but not required.

We are seeking a Software Engineer to help develop AI solutions. In this role, you will ensure that software is developed to meet functional, non-functional and compliance requirements, and solutions are well designed with maintainability/ease of integration and testing built-in from the outset.

This includes requirements analysis, architecture design, coding, testing, and deployment. Job expectations include a considerable amount of knowledge of development and testing practices common to the industry and design and architectural patterns.

Responsibilities:

  • Design, develop, and enhance core Agent Runtime capabilities and reusable platform services that enable the development, deployment, orchestration, and management of AI agents.
  • Implement agent platform features, including tool integration frameworks, orchestration logic, memory management, context management, and runtime execution capabilities.
  • Develop and maintain platform controls, guardrails, policy enforcement mechanisms, and safety capabilities to support secure and compliant use of Generative AI solutions.
  • Build and enhance evaluation frameworks, automated testing capabilities, benchmarking tools, and observability solutions to measure agent quality, reliability, safety, and performance.
  • Design and implement APIs, SDKs, and platform components that enable scalable adoption of agent capabilities across engineering teams.
  • Translate business, product, and technical requirements into robust software solutions while adhering to enterprise architecture, security, and compliance standards.
  • Execute story refinement, technical analysis, solution design, and effort estimation activities throughout the software development lifecycle.
  • Perform proof-of-concept development and technical experimentation to evaluate emerging AI technologies, frameworks, and design patterns.
  • Develop and maintain automated unit, integration, regression, performance, and evaluation test suites to ensure platform stability and reliability.
  • Troubleshoot and resolve complex issues involving agent execution, model integration, runtime performance, scaling, observability, and platform operations.
  • Optimize platform components for performance, reliability, scalability, and cost efficiency across production environments.
  • Conduct peer code reviews and contribute to engineering standards, development practices, and reusable patterns that improve overall platform quality.
  • Ensure delivered solutions meet defined expectations for functionality, security, governance, quality, reliability, and operational supportability.

Experience Required:

  • 7+ years of professional software engineering experience designing, developing, and supporting enterprise-grade applications and platform services.
  • Strong experience developing Python-based services using FastAPI, asynchronous programming patterns (async/await), API design, dependency injection, background processing, and integration with external systems and services.
  • Experience developing reusable platform capabilities, SDKs, frameworks, or shared services used by multiple engineering teams.
  • Experience implementing security controls, policy enforcement, guardrails, governance capabilities, and observability solutions for enterprise applications.
  • Experience designing and implementing automated testing frameworks, including unit, integration, regression, performance, and evaluation testing.
  • Experience developing CI/CD pipelines and automating software build, deployment, and release processes.
  • Strong troubleshooting and debugging skills with the ability to diagnose and resolve complex application, runtime, performance, and integration issues.
  • Experience working in Agile development environments and participating in requirements analysis, technical design, estimation, and software delivery.
  • Strong analytical, problem-solving, and communication skills with the ability to work effectively across engineering, product, and architecture teams.

Experience Desired (not essential):

  • Kubernetes/OpenShift
  • Kafka and event-driven architecture
  • MongoDB and Redis
  • LangChain, LangGraph, or similar agent frameworks
  • OpenTelemetry and Splunk
  • Galileo, LangSmith, or similar AI evaluation and observability tools

A full-time year is 2,080 hours: $33 an hour is $68,640 a year before taxes, and $66,000 a year is $31.73 an hour. Pay calculator →

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