What are the responsibilities and job description for the Software Engineer Python - Advanced position at Photon?
Job Title: Software Engineer Python - Advanced
Location: Columbus OH
Job Description:
- We are looking for an Advanced Python Engineer / Agentic AI FDE with strong hands-on experience in Python development and a solid understanding of Generative AI, LLMs, AI Agents, and agentic application development.
- The ideal candidate will work closely with client engineering and product teams to design, develop, integrate, and deploy production-grade agentic AI solutions. This role requires strong software engineering fundamentals, the ability to work with modern AI frameworks, and excellent client-facing problem-solving skills.
Key Responsibilities:
- Design and develop scalable Agentic AI applications and AI-powered solutions using Python.
- Build, integrate, and optimize AI agents, multi-agent workflows, tools, and orchestration pipelines.
- Develop production-grade Python services, APIs, integrations, and backend components.
- Work with LLMs, prompt engineering, RAG, embeddings, vector databases, and tool/function calling.
- Implement agent workflows using frameworks such as LangChain, LangGraph, OpenAI Agent SDK, Google ADK, CrewAI, AutoGen, or similar frameworks.
- Integrate AI agents with enterprise systems, APIs, databases, SaaS platforms, and business applications.
- Develop and consume REST APIs, microservices, and event-driven integrations.
- Implement appropriate mechanisms for agent memory, context management, state management, and knowledge retrieval.
- Work with cloud-based AI platforms such as AWS Bedrock, Azure AI Foundry, or Google Cloud Vertex AI/Gemini.
- Implement observability, monitoring, logging, evaluation, and performance optimization for AI applications.
- Collaborate with architects, product managers, data scientists, and client stakeholders to translate business requirements into technical solutions.
- Participate in client discussions, technical workshops, solution demonstrations, and proof-of-concepts.
- Troubleshoot complex technical issues and provide hands-on engineering support during implementation.
- Follow secure and responsible AI engineering practices, including appropriate authentication, authorization, data protection, and AI governance.
Required Technical Skills:
Python Advanced:
- Strong hands-on expertise in Python.
- Advanced knowledge of Python programming concepts, OOP, data structures, exception handling, concurrency/asynchronous programming, and performance optimization.
- Experience building production-grade applications and APIs using frameworks such as FastAPI, Flask, or Django.
- Strong understanding of testing, debugging, logging, packaging, and dependency management.
Agentic AI / Generative AI:
- Strong understanding of LLMs, Generative AI, AI Agents, Agentic AI, and LLM application architecture.
- Hands-on experience with one or more agent frameworks such as:
- LangChain / LangGraph
- OpenAI Agent SDK
- Google ADK
- CrewAI
- AutoGen
- Microsoft Agent Framework or equivalent
- Experience with RAG, vector search, embeddings, prompt engineering, tool/function calling, structured outputs, and agent orchestration.
- Understanding of agent memory, context management, multi-agent systems, and agent evaluation.
Cloud & AI Platforms:
- Experience with at least one major cloud platform: AWS, Azure, or Google Cloud Platform.
- Exposure to AI platforms such as Amazon Bedrock, Azure AI Foundry, Vertex AI/Gemini, or equivalent.
- Understanding of deploying AI applications in cloud environments.
APIs & Integration:
- Strong experience with REST APIs, JSON, web services, authentication, and third-party integrations.
- Experience integrating AI solutions with enterprise applications and data sources.
- Understanding of microservices and distributed application architecture.
Data & Databases:
- Experience with SQL and relational databases.
- Exposure to NoSQL databases and vector databases such as Pinecone, Weaviate, Milvus, pgvector, or equivalent.
- Understanding of data ingestion, retrieval, chunking, embeddings, and knowledge bases.
Preferred Skills:
- Experience with Docker, Kubernetes, CI/CD, Git, and cloud deployment.
- Exposure to AI observability and evaluation tools.
- Understanding of AI governance, guardrails, responsible AI, and security considerations for agentic systems.
- Experience with MCP (Model Context Protocol) and enterprise tool integrations.
- Experience working with enterprise-grade AI platforms or agent orchestration platforms.
- Knowledge of authentication and authorization mechanisms such as OAuth2/JWT.
- Experience working in financial services, banking, or other highly regulated environments is a plus.
FDE / Client-Facing Skills:
- Strong communication and stakeholder management skills.
- Ability to work directly with client engineering, architecture, and product teams.
- Ability to understand ambiguous business problems and convert them into technical solutions.
- Comfortable conducting technical workshops, architecture discussions, POCs, demos, and troubleshooting sessions.
- Ability to work independently in a fast-paced client environment.
- Strong analytical and problem-solving skills.
Education & Experience:
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline.
- 5 years of software engineering experience, with strong hands-on Python development experience.
- 2 years of experience in Generative AI / LLM / Agentic AI development preferred.
- Proven experience delivering production-grade applications or AI solutions.
Key Competencies:
Python | Agentic AI | Generative AI | LLMs | AI Agents | LangChain | LangGraph | OpenAI Agent SDK | RAG | Prompt Engineering | Vector Databases | FastAPI | REST APIs | AWS/Azure/Google Cloud Platform | Bedrock | Azure AI Foundry | Vertex AI | Docker | Kubernetes | CI/CD | AI Governance | Client Engineering | FDE
Salary : $60 - $70