Develop production-grade agentic AI applications in Python, including AI agents, multi-agent workflows, APIs, integrations, RAG pipelines, and cloud deployments. Use LLMs, vector databases, agent frameworks, and observability tools while implementing secure, governed AI solutions. Collaborate with clients, architects, product teams, and data scientists through workshops, demonstrations, proofs of concept, and troubleshooting sessions.
Software Engineering – Python – Advanced Role Overview
We are looking for an experienced Python Software Engineer to design, develop, and maintain scalable, high-performance software solutions. The ideal candidate should have strong hands-on expertise in Python development, backend engineering, API development, cloud technologies, and modern software engineering practices.
Key Responsibilities- Design, develop, test, and maintain scalable applications and backend services using Python.
- Build robust and reusable components, APIs, microservices, and integrations.
- Develop RESTful APIs and integrate with internal and external systems.
- Write clean, maintainable, well-tested, and production-ready code.
- Troubleshoot complex technical issues and optimize application performance.
- Work with databases, data models, caching, and asynchronous processing.
- Implement secure coding practices, authentication, authorization, and API security.
- Collaborate with Product Managers, Architects, DevOps, QA, and other engineering teams.
- Participate in code reviews, technical design discussions, and architecture decisions.
- Develop automated unit, integration, and functional tests.
- Work with CI/CD pipelines and modern DevOps practices.
- Monitor applications in production and support troubleshooting and root-cause analysis.
- Contribute to technical documentation and engineering best practices.
- Advanced proficiency in Python with strong knowledge of Python 3.x.
- Strong understanding of object-oriented programming, data structures, algorithms, and design patterns.
- Experience with Python frameworks such as FastAPI, Flask, or Django.
- Strong experience developing REST APIs and microservices.
- Good understanding of SQL and relational databases such as PostgreSQL, MySQL, or Oracle.
- Experience with NoSQL databases such as MongoDB, DynamoDB, or Redis is preferred.
- Strong knowledge of Git and version-control practices.
- Experience with unit testing frameworks such as PyTest or unittest.
- Knowledge of asynchronous programming using asyncio and related Python frameworks.
- Experience with Docker and containerized application development.
- Understanding of CI/CD and DevOps practices.
- Strong debugging, problem-solving, and performance-optimization skills.
- Experience working with at least one major cloud platform: AWS, Azure, or GCP.
- Understanding of cloud-native application development and distributed systems.
- Experience with messaging/event-driven technologies such as Kafka, RabbitMQ, or SQS is preferred.
- Familiarity with Kubernetes and container orchestration is a plus.
- Exposure to observability tools, logging, monitoring, and application performance management.
- Exposure to Generative AI, LLMs, or AI-enabled applications is preferred.
- Experience integrating LLM APIs or AI services into Python applications is a plus.
- Familiarity with frameworks such as LangChain, LangGraph, OpenAI SDK, or similar agentic AI frameworks is desirable.
- Understanding of API-based integration with AI/ML platforms and model-serving infrastructure is an advantage.
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field.
- Typically 5+ years of software engineering experience, with strong hands-on Python development experience.
- Experience working in Agile/Scrum development environments.
- Strong communication and collaboration skills.
- Ability to independently analyze complex technical problems and deliver scalable solutions.
- Experience designing highly scalable distributed systems.
- Knowledge of system design and software architecture.
- Experience with event-driven and asynchronous architectures.
- Experience in financial services, enterprise applications, or other large-scale environments.
- Exposure to security, observability, and performance engineering.
Compensation, Benefits and Duration
Minimum Compensation: USD 42,000
Maximum Compensation: USD 147,000
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 available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
Photon New York, New York, USA Office
New York, United States
Similar Jobs
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.
Top Skills:
AnsibleAWSCassandraChefDockerElasticsearchGCPGpuGpu-ClustersJvmKafkaKubernetesMaasPythonSparkTerraform
Blockchain • Fintech • Payments • Financial Services • Cryptocurrency • Web3
Leads Circle’s third-party security program by conducting complex partner and vendor assessments, evaluating technical controls, identifying risks, and communicating recommendations. Builds AI-enabled tooling, automation, monitoring, scoring, and intelligence-driven workflows to modernize security reviews and support continuous risk management. Partners with Security Engineering, Legal, Procurement, and business teams to embed security requirements into third-party onboarding and oversight.
Top Skills:
AIApi SecurityBlockchainCloud SecurityCryptographyDoraGenerative AiIdentity And Access ManagementIso 27001Network ArchitectureSecurity AutomationSmart ContractsSoc 2
Automotive • Professional Services • Software • Consulting • Energy • Chemical • Renewable Energy
Lead functional safety consulting for vehicle, autonomous systems, industrial automation, battery, and energy storage programs. Develop safety concepts, requirements, safety cases, hazard analyses, and hardware and software safety work products. Perform FMEA, FMEDA, FTA, STPA, and DFA assessments while ensuring compliance with functional safety standards. Lead workshops, training, client reviews, technical assessments, and confirmation measures. Support business development through statements of work, estimates, proposals, and industry representation. Occasional travel to client sites may be required.
Top Skills:
DfaFmeaFmedaFtaHaraIec 61508Iec/En 62061Iso 13849Iso 21448Iso 26262Iso 61511StpaUl 4600
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
