Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

Python/AI Engineer 18 Month W2 Contract NYC- Hyrbird 3 days onsite $60-$68/hour

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